{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"machine_shape":"hm","gpuType":"L4","authorship_tag":"ABX9TyMYWRFk02CUZBNl6l6UdpOA"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"},"accelerator":"GPU"},"cells":[{"cell_type":"code","execution_count":2,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"bL7t-1eNclGx","executionInfo":{"status":"ok","timestamp":1726986885463,"user_tz":-480,"elapsed":4097,"user":{"displayName":"李辉","userId":"12972001611808140221"}},"outputId":"e9da3271-f977-4b34-a0eb-9632922f2ac3"},"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: langchain-nomic in /usr/local/lib/python3.10/dist-packages (0.1.3)\n","Requirement already satisfied: langchain_community in /usr/local/lib/python3.10/dist-packages (0.3.0)\n","Requirement already satisfied: tiktoken in /usr/local/lib/python3.10/dist-packages (0.7.0)\n","Requirement already 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/usr/local/lib/python3.10/dist-packages (from pyasn1-modules>=0.2.1->google-auth>=1.0.1->kubernetes>=28.1.0->chromadb) (0.6.1)\n"]}],"source":["%pip install -U langchain-nomic langchain_community tiktoken langchainhub chromadb langchain langgraph tavily-python nomic[local]"]},{"cell_type":"markdown","source":["下载ollama"],"metadata":{"id":"XGZjD9fRqTxY"}},{"cell_type":"code","source":["! sudo apt-get install -y pciutils\n","! curl https://ollama.ai/install.sh | sh"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"07NS5Q_YgolU","executionInfo":{"status":"ok","timestamp":1726987009983,"user_tz":-480,"elapsed":39288,"user":{"displayName":"李辉","userId":"12972001611808140221"}},"outputId":"e69c8b82-a458-4019-f013-1c1beef27a34"},"execution_count":3,"outputs":[{"output_type":"stream","name":"stdout","text":["Reading package lists... Done\n","Building dependency tree... Done\n","Reading state information... Done\n","The following additional packages will be installed:\n","  libpci3 pci.ids\n","The following NEW packages will be installed:\n","  libpci3 pci.ids pciutils\n","0 upgraded, 3 newly installed, 0 to remove and 49 not upgraded.\n","Need to get 343 kB of archives.\n","After this operation, 1,581 kB of additional disk space will be used.\n","Get:1 http://archive.ubuntu.com/ubuntu jammy/main amd64 pci.ids all 0.0~2022.01.22-1 [251 kB]\n","Get:2 http://archive.ubuntu.com/ubuntu jammy/main amd64 libpci3 amd64 1:3.7.0-6 [28.9 kB]\n","Get:3 http://archive.ubuntu.com/ubuntu jammy/main amd64 pciutils amd64 1:3.7.0-6 [63.6 kB]\n","Fetched 343 kB in 1s (276 kB/s)\n","debconf: unable to initialize frontend: Dialog\n","debconf: (No usable dialog-like program is installed, so the dialog based frontend cannot be used. at /usr/share/perl5/Debconf/FrontEnd/Dialog.pm line 78, <> line 3.)\n","debconf: falling back to frontend: Readline\n","debconf: unable to initialize frontend: Readline\n","debconf: (This frontend requires a controlling tty.)\n","debconf: falling back to frontend: Teletype\n","dpkg-preconfigure: unable to re-open stdin: \n","Selecting previously unselected package pci.ids.\n","(Reading database ... 123599 files and directories currently installed.)\n","Preparing to unpack .../pci.ids_0.0~2022.01.22-1_all.deb ...\n","Unpacking pci.ids (0.0~2022.01.22-1) ...\n","Selecting previously unselected package libpci3:amd64.\n","Preparing to unpack .../libpci3_1%3a3.7.0-6_amd64.deb ...\n","Unpacking libpci3:amd64 (1:3.7.0-6) ...\n","Selecting previously unselected package pciutils.\n","Preparing to unpack .../pciutils_1%3a3.7.0-6_amd64.deb ...\n","Unpacking pciutils (1:3.7.0-6) ...\n","Setting up pci.ids (0.0~2022.01.22-1) ...\n","Setting up libpci3:amd64 (1:3.7.0-6) ...\n","Setting up pciutils (1:3.7.0-6) ...\n","Processing triggers for man-db (2.10.2-1) ...\n","Processing triggers for libc-bin (2.35-0ubuntu3.4) ...\n","/sbin/ldconfig.real: /usr/local/lib/libtbb.so.12 is not a symbolic link\n","\n","/sbin/ldconfig.real: /usr/local/lib/libtbbbind_2_5.so.3 is not a symbolic link\n","\n","/sbin/ldconfig.real: /usr/local/lib/libtbbbind_2_0.so.3 is not a symbolic link\n","\n","/sbin/ldconfig.real: /usr/local/lib/libtbbbind.so.3 is not a symbolic link\n","\n","/sbin/ldconfig.real: /usr/local/lib/libtbbmalloc_proxy.so.2 is not a symbolic link\n","\n","/sbin/ldconfig.real: /usr/local/lib/libtbbmalloc.so.2 is not a symbolic link\n","\n","/sbin/ldconfig.real: /usr/local/lib/libur_adapter_level_zero.so.0 is not a symbolic link\n","\n","/sbin/ldconfig.real: /usr/local/lib/libur_loader.so.0 is not a symbolic link\n","\n","/sbin/ldconfig.real: /usr/local/lib/libur_adapter_opencl.so.0 is not a symbolic link\n","\n","  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n","                                 Dload  Upload   Total   Spent    Left  Speed\n","  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0>>> Installing ollama to /usr/local\n","100 13320    0 13320    0     0  31985      0 --:--:-- --:--:-- --:--:-- 32019\n",">>> Downloading Linux amd64 bundle\n","############################################################################################# 100.0%\n",">>> Creating ollama user...\n",">>> Adding ollama user to video group...\n",">>> Adding current user to ollama group...\n",">>> Creating ollama systemd service...\n",">>> NVIDIA GPU installed.\n",">>> The Ollama API is now available at 127.0.0.1:11434.\n",">>> Install complete. Run \"ollama\" from the command line.\n"]}]},{"cell_type":"markdown","source":["后台运行不打印日志，如果需要打印日志可以添加配置文件启动"],"metadata":{"id":"v90SeejCqYvL"}},{"cell_type":"code","source":["! nohup ollama serve >/dev/null 2>&1 &\n"],"metadata":{"id":"5C7cJISsgxKT","executionInfo":{"status":"ok","timestamp":1726987024624,"user_tz":-480,"elapsed":734,"user":{"displayName":"李辉","userId":"12972001611808140221"}}},"execution_count":4,"outputs":[]},{"cell_type":"code","source":["! ollama --version\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ZwGb-InkkbvV","executionInfo":{"status":"ok","timestamp":1726987045285,"user_tz":-480,"elapsed":780,"user":{"displayName":"李辉","userId":"12972001611808140221"}},"outputId":"3922a421-cb31-4d88-c12a-5315d7b18b78"},"execution_count":5,"outputs":[{"output_type":"stream","name":"stdout","text":["ollama version is 0.3.11\n"]}]},{"cell_type":"markdown","source":["拉取模型"],"metadata":{"id":"9O6nigwMrCCZ"}},{"cell_type":"code","source":["! ollama pull mistral"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"sAN4mWeBlL6t","executionInfo":{"status":"ok","timestamp":1726987134320,"user_tz":-480,"elapsed":66116,"user":{"displayName":"李辉","userId":"12972001611808140221"}},"outputId":"0e8d14f0-e9ea-422e-897f-587da2c173ac","collapsed":true},"execution_count":6,"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[?25lpulling manifest ⠋ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest ⠙ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest ⠹ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest ⠸ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest ⠴ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest ⠴ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest ⠦ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest ⠇ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest ⠇ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest ⠏ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling 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\n","pulling ff82381e2bea...  16% ▕▏ 664 MB/4.1 GB  154 MB/s     22s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  17% ▕▏ 711 MB/4.1 GB  154 MB/s     22s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  18% ▕▏ 738 MB/4.1 GB  154 MB/s     21s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  19% ▕▏ 797 MB/4.1 GB  154 MB/s     21s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  21% ▕▏ 844 MB/4.1 GB  211 MB/s     15s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  21% ▕▏ 875 MB/4.1 GB  211 MB/s     15s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  22% ▕▏ 914 MB/4.1 GB  211 MB/s     15s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  24% ▕▏ 968 MB/4.1 GB  211 MB/s     14s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  24% ▕▏ 990 MB/4.1 GB  211 MB/s     14s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  25% ▕▏ 1.0 GB/4.1 GB  211 MB/s     14s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  26% ▕▏ 1.1 GB/4.1 GB  211 MB/s     14s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  27% ▕▏ 1.1 GB/4.1 GB  211 MB/s     14s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  28% ▕▏ 1.2 GB/4.1 GB  211 MB/s     13s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  29% ▕▏ 1.2 GB/4.1 GB  211 MB/s     13s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  30% ▕▏ 1.2 GB/4.1 GB  211 MB/s     13s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  31% ▕▏ 1.3 GB/4.1 GB  250 MB/s     11s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  32% ▕▏ 1.3 GB/4.1 GB  250 MB/s     11s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  33% ▕▏ 1.4 GB/4.1 GB  250 MB/s     11s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  34% ▕▏ 1.4 GB/4.1 GB  250 MB/s     10s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  35% ▕▏ 1.5 GB/4.1 GB  250 MB/s     10s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  36% ▕▏ 1.5 GB/4.1 GB  250 MB/s     10s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  37% ▕▏ 1.5 GB/4.1 GB  250 MB/s     10s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  38% ▕▏ 1.6 GB/4.1 GB  250 MB/s     10s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  39% ▕▏ 1.6 GB/4.1 GB  250 MB/s     10s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  40% ▕▏ 1.7 GB/4.1 GB  250 MB/s      9s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  41% ▕▏ 1.7 GB/4.1 GB  279 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  42% ▕▏ 1.7 GB/4.1 GB  279 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  43% ▕▏ 1.8 GB/4.1 GB  279 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  44% ▕▏ 1.8 GB/4.1 GB  279 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  44% ▕▏ 1.8 GB/4.1 GB  279 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  46% ▕▏ 1.9 GB/4.1 GB  279 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  46% ▕▏ 1.9 GB/4.1 GB  279 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  47% ▕▏ 1.9 GB/4.1 GB  279 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  48% ▕▏ 2.0 GB/4.1 GB  279 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  48% ▕▏ 2.0 GB/4.1 GB  279 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  49% ▕▏ 2.0 GB/4.1 GB  289 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  50% ▕▏ 2.0 GB/4.1 GB  289 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  51% ▕▏ 2.1 GB/4.1 GB  289 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  52% ▕▏ 2.1 GB/4.1 GB  289 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  53% ▕▏ 2.2 GB/4.1 GB  289 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  53% ▕▏ 2.2 GB/4.1 GB  289 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  54% ▕▏ 2.2 GB/4.1 GB  289 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  55% ▕▏ 2.3 GB/4.1 GB  289 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  56% ▕▏ 2.3 GB/4.1 GB  289 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  56% ▕▏ 2.3 GB/4.1 GB  289 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  57% ▕▏ 2.3 GB/4.1 GB  293 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  58% ▕▏ 2.4 GB/4.1 GB  293 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  58% ▕▏ 2.4 GB/4.1 GB  293 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  59% ▕▏ 2.4 GB/4.1 GB  293 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  60% ▕▏ 2.5 GB/4.1 GB  293 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  60% ▕▏ 2.5 GB/4.1 GB  293 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  61% ▕▏ 2.5 GB/4.1 GB  293 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  62% ▕▏ 2.5 GB/4.1 GB  293 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  62% ▕▏ 2.5 GB/4.1 GB  293 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  63% ▕▏ 2.6 GB/4.1 GB  293 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  64% ▕▏ 2.6 GB/4.1 GB  292 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  64% ▕▏ 2.6 GB/4.1 GB  292 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  64% ▕▏ 2.6 GB/4.1 GB  292 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  64% ▕▏ 2.7 GB/4.1 GB  292 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  65% ▕▏ 2.7 GB/4.1 GB  292 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  65% ▕▏ 2.7 GB/4.1 GB  292 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  65% ▕▏ 2.7 GB/4.1 GB  292 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  66% ▕▏ 2.7 GB/4.1 GB  292 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  68% ▕▏ 2.8 GB/4.1 GB  292 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  70% ▕▏ 2.9 GB/4.1 GB  292 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  71% ▕▏ 2.9 GB/4.1 GB  292 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  71% ▕▏ 2.9 GB/4.1 GB  320 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  72% ▕▏ 3.0 GB/4.1 GB  320 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  73% ▕▏ 3.0 GB/4.1 GB  320 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  73% ▕▏ 3.0 GB/4.1 GB  320 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  73% ▕▏ 3.0 GB/4.1 GB  320 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  74% ▕▏ 3.1 GB/4.1 GB  320 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  75% ▕▏ 3.1 GB/4.1 GB  320 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  75% ▕▏ 3.1 GB/4.1 GB  320 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  75% ▕▏ 3.1 GB/4.1 GB  320 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  77% ▕▏ 3.2 GB/4.1 GB  320 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  78% ▕▏ 3.2 GB/4.1 GB  332 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  79% ▕▏ 3.2 GB/4.1 GB  332 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  80% ▕▏ 3.3 GB/4.1 GB  332 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  80% ▕▏ 3.3 GB/4.1 GB  332 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  81% ▕▏ 3.3 GB/4.1 GB  332 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  82% ▕▏ 3.4 GB/4.1 GB  332 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  82% ▕▏ 3.4 GB/4.1 GB  332 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  82% ▕▏ 3.4 GB/4.1 GB  332 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  83% ▕▏ 3.4 GB/4.1 GB  332 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  83% ▕▏ 3.4 GB/4.1 GB  332 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  83% ▕▏ 3.4 GB/4.1 GB  328 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  83% ▕▏ 3.4 GB/4.1 GB  328 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  83% ▕▏ 3.4 GB/4.1 GB  328 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  84% ▕▏ 3.4 GB/4.1 GB  328 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  84% ▕▏ 3.4 GB/4.1 GB  328 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  84% ▕▏ 3.4 GB/4.1 GB  328 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  84% ▕▏ 3.4 GB/4.1 GB  328 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  84% ▕▏ 3.5 GB/4.1 GB  328 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  84% ▕▏ 3.5 GB/4.1 GB  328 MB/s      1s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  84% ▕▏ 3.5 GB/4.1 GB  328 MB/s      1s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  84% ▕▏ 3.5 GB/4.1 GB  291 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  84% ▕▏ 3.5 GB/4.1 GB  291 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  84% ▕▏ 3.5 GB/4.1 GB  291 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  85% ▕▏ 3.5 GB/4.1 GB  291 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  85% ▕▏ 3.5 GB/4.1 GB  291 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  85% ▕▏ 3.5 GB/4.1 GB  291 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  85% ▕▏ 3.5 GB/4.1 GB  291 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  85% ▕▏ 3.5 GB/4.1 GB  291 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  85% ▕▏ 3.5 GB/4.1 GB  291 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  85% ▕▏ 3.5 GB/4.1 GB  291 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  85% ▕▏ 3.5 GB/4.1 GB  250 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  85% ▕▏ 3.5 GB/4.1 GB  250 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  86% ▕▏ 3.5 GB/4.1 GB  250 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  86% ▕▏ 3.5 GB/4.1 GB  250 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  86% ▕▏ 3.5 GB/4.1 GB  250 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  86% ▕▏ 3.5 GB/4.1 GB  250 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  86% ▕▏ 3.5 GB/4.1 GB  250 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  86% ▕▏ 3.5 GB/4.1 GB  250 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  86% ▕▏ 3.6 GB/4.1 GB  250 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  87% ▕▏ 3.6 GB/4.1 GB  250 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  87% ▕▏ 3.6 GB/4.1 GB  250 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  87% ▕▏ 3.6 GB/4.1 GB  209 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  87% ▕▏ 3.6 GB/4.1 GB  209 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  87% ▕▏ 3.6 GB/4.1 GB  209 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  87% ▕▏ 3.6 GB/4.1 GB  209 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  87% ▕▏ 3.6 GB/4.1 GB  209 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  87% ▕▏ 3.6 GB/4.1 GB  209 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  87% ▕▏ 3.6 GB/4.1 GB  209 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  87% ▕▏ 3.6 GB/4.1 GB  209 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  87% ▕▏ 3.6 GB/4.1 GB  209 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  87% ▕▏ 3.6 GB/4.1 GB  209 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  87% ▕▏ 3.6 GB/4.1 GB  174 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  87% ▕▏ 3.6 GB/4.1 GB  174 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  88% ▕▏ 3.6 GB/4.1 GB  174 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  88% ▕▏ 3.6 GB/4.1 GB  174 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  88% ▕▏ 3.6 GB/4.1 GB  174 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  88% ▕▏ 3.6 GB/4.1 GB  174 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  88% ▕▏ 3.6 GB/4.1 GB  174 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  88% ▕▏ 3.6 GB/4.1 GB  174 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  88% ▕▏ 3.6 GB/4.1 GB  174 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  88% ▕▏ 3.6 GB/4.1 GB  174 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  88% ▕▏ 3.6 GB/4.1 GB  142 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  88% ▕▏ 3.6 GB/4.1 GB  142 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  88% ▕▏ 3.6 GB/4.1 GB  142 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  88% ▕▏ 3.6 GB/4.1 GB  142 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  89% ▕▏ 3.6 GB/4.1 GB  142 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  89% ▕▏ 3.6 GB/4.1 GB  142 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  89% ▕▏ 3.6 GB/4.1 GB  142 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  89% ▕▏ 3.7 GB/4.1 GB  142 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  89% ▕▏ 3.7 GB/4.1 GB  142 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  89% ▕▏ 3.7 GB/4.1 GB  142 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  89% ▕▏ 3.7 GB/4.1 GB  113 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  89% ▕▏ 3.7 GB/4.1 GB  113 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  89% ▕▏ 3.7 GB/4.1 GB  113 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  89% ▕▏ 3.7 GB/4.1 GB  113 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  89% ▕▏ 3.7 GB/4.1 GB  113 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  89% ▕▏ 3.7 GB/4.1 GB  113 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  89% ▕▏ 3.7 GB/4.1 GB  113 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  90% ▕▏ 3.7 GB/4.1 GB  113 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  90% ▕▏ 3.7 GB/4.1 GB  113 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  90% ▕▏ 3.7 GB/4.1 GB  113 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  90% ▕▏ 3.7 GB/4.1 GB   86 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  90% ▕▏ 3.7 GB/4.1 GB   86 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  90% ▕▏ 3.7 GB/4.1 GB   86 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  90% ▕▏ 3.7 GB/4.1 GB   86 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  90% ▕▏ 3.7 GB/4.1 GB   86 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  90% ▕▏ 3.7 GB/4.1 GB   86 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  90% ▕▏ 3.7 GB/4.1 GB   86 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  90% ▕▏ 3.7 GB/4.1 GB   86 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  90% ▕▏ 3.7 GB/4.1 GB   86 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  91% ▕▏ 3.7 GB/4.1 GB   86 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  91% ▕▏ 3.7 GB/4.1 GB   86 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  91% ▕▏ 3.7 GB/4.1 GB   58 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  91% ▕▏ 3.7 GB/4.1 GB   58 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  91% ▕▏ 3.7 GB/4.1 GB   58 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  91% ▕▏ 3.7 GB/4.1 GB   58 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  91% ▕▏ 3.7 GB/4.1 GB   58 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  91% ▕▏ 3.7 GB/4.1 GB   58 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  91% ▕▏ 3.8 GB/4.1 GB   58 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  91% ▕▏ 3.8 GB/4.1 GB   58 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  91% ▕▏ 3.8 GB/4.1 GB   58 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  91% ▕▏ 3.8 GB/4.1 GB   58 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  92% ▕▏ 3.8 GB/4.1 GB   38 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  92% ▕▏ 3.8 GB/4.1 GB   38 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  92% ▕▏ 3.8 GB/4.1 GB   38 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  92% ▕▏ 3.8 GB/4.1 GB   38 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  92% ▕▏ 3.8 GB/4.1 GB   38 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  92% ▕▏ 3.8 GB/4.1 GB   38 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  92% ▕▏ 3.8 GB/4.1 GB   38 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  92% ▕▏ 3.8 GB/4.1 GB   38 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  92% ▕▏ 3.8 GB/4.1 GB   38 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  92% ▕▏ 3.8 GB/4.1 GB   38 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  92% ▕▏ 3.8 GB/4.1 GB   37 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  93% ▕▏ 3.8 GB/4.1 GB   37 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  93% ▕▏ 3.8 GB/4.1 GB   37 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  93% ▕▏ 3.8 GB/4.1 GB   37 MB/s      8s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  93% ▕▏ 3.8 GB/4.1 GB   37 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  93% ▕▏ 3.8 GB/4.1 GB   37 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  93% ▕▏ 3.8 GB/4.1 GB   37 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  93% ▕▏ 3.8 GB/4.1 GB   37 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  93% ▕▏ 3.8 GB/4.1 GB   37 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  93% ▕▏ 3.8 GB/4.1 GB   37 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  93% ▕▏ 3.8 GB/4.1 GB   36 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.8 GB/4.1 GB   36 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.8 GB/4.1 GB   36 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.8 GB/4.1 GB   36 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.9 GB/4.1 GB   36 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.9 GB/4.1 GB   36 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.9 GB/4.1 GB   36 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.9 GB/4.1 GB   36 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.9 GB/4.1 GB   36 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.9 GB/4.1 GB   36 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.9 GB/4.1 GB   33 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.9 GB/4.1 GB   33 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.9 GB/4.1 GB   33 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.9 GB/4.1 GB   33 MB/s      7s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.9 GB/4.1 GB   33 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.9 GB/4.1 GB   33 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.9 GB/4.1 GB   33 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  94% ▕▏ 3.9 GB/4.1 GB   33 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  95% ▕▏ 3.9 GB/4.1 GB   33 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  95% ▕▏ 3.9 GB/4.1 GB   33 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  95% ▕▏ 3.9 GB/4.1 GB   33 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  95% ▕▏ 3.9 GB/4.1 GB   33 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  95% ▕▏ 3.9 GB/4.1 GB   33 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  95% ▕▏ 3.9 GB/4.1 GB   33 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  95% ▕▏ 3.9 GB/4.1 GB   33 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  95% ▕▏ 3.9 GB/4.1 GB   33 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  95% ▕▏ 3.9 GB/4.1 GB   33 MB/s      6s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  95% ▕▏ 3.9 GB/4.1 GB   33 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  95% ▕▏ 3.9 GB/4.1 GB   33 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  95% ▕▏ 3.9 GB/4.1 GB   33 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  95% ▕▏ 3.9 GB/4.1 GB   33 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  95% ▕▏ 3.9 GB/4.1 GB   33 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  95% ▕▏ 3.9 GB/4.1 GB   33 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  96% ▕▏ 3.9 GB/4.1 GB   33 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  96% ▕▏ 3.9 GB/4.1 GB   33 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  96% ▕▏ 3.9 GB/4.1 GB   33 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  96% ▕▏ 3.9 GB/4.1 GB   33 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  96% ▕▏ 3.9 GB/4.1 GB   33 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  96% ▕▏ 3.9 GB/4.1 GB   33 MB/s      5s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  96% ▕▏ 3.9 GB/4.1 GB   33 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  96% ▕▏ 4.0 GB/4.1 GB   33 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  96% ▕▏ 4.0 GB/4.1 GB   32 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  96% ▕▏ 4.0 GB/4.1 GB   32 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  96% ▕▏ 4.0 GB/4.1 GB   32 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  96% ▕▏ 4.0 GB/4.1 GB   32 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   32 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   29 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   29 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   29 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   29 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   29 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   29 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   29 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   29 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   29 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   29 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   29 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   26 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   26 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   26 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   26 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   26 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   26 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   26 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  97% ▕▏ 4.0 GB/4.1 GB   26 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   26 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   26 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   23 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   23 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   23 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   23 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   23 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   23 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   23 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   23 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   23 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   23 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   20 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   20 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   20 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   20 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   20 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   20 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   20 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   20 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   20 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   20 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   18 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   18 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   18 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   18 MB/s      4s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   18 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   18 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   18 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   18 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   18 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   18 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.0 GB/4.1 GB   16 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.1 GB/4.1 GB   16 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  98% ▕▏ 4.1 GB/4.1 GB   16 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   16 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   16 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   16 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   16 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   16 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   16 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   16 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   16 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   15 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   15 MB/s      3s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   15 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   15 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   15 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   15 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   15 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   15 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   15 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   15 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   13 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   13 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   13 MB/s      2s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   13 MB/s      1s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   13 MB/s      1s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   13 MB/s      1s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   13 MB/s      1s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea...  99% ▕▏ 4.1 GB/4.1 GB   13 MB/s      1s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   13 MB/s      1s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   13 MB/s      1s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      1s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      1s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      1s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest 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MB/s      0s\n","pulling 43070e2d4e53...   0% ▕▏    0 B/ 11 KB                  \u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\n","pulling 43070e2d4e53...   0% ▕▏    0 B/ 11 KB                  \u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\n","pulling 43070e2d4e53...   0% ▕▏    0 B/ 11 KB                  \u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\n","pulling 43070e2d4e53...   0% ▕▏    0 B/ 11 KB                  \u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\n","pulling 43070e2d4e53... 100% ▕▏  11 KB                         \u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\n","pulling 43070e2d4e53... 100% ▕▏  11 KB                         \u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\n","pulling 43070e2d4e53... 100% ▕▏  11 KB                         \u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\n","pulling 43070e2d4e53... 100% ▕▏  11 KB                         \u001b[?25h\u001b[?25l\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1G\u001b[A\u001b[2K\u001b[1Gpulling manifest \n","pulling ff82381e2bea... 100% ▕▏ 4.1 GB/4.1 GB   12 MB/s      0s\n","pulling 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userdata.get('LANGCHAIN_API_KEY')"],"metadata":{"id":"qndvDUsuluRX","executionInfo":{"status":"ok","timestamp":1726987158256,"user_tz":-480,"elapsed":2579,"user":{"displayName":"李辉","userId":"12972001611808140221"}}},"execution_count":7,"outputs":[]},{"cell_type":"code","source":["os.environ[\"TAVILY_API_KEY\"] = userdata.get('TAVILY_API_KEY')"],"metadata":{"id":"5cGbtOV2oi2I","executionInfo":{"status":"ok","timestamp":1726987166316,"user_tz":-480,"elapsed":3142,"user":{"displayName":"李辉","userId":"12972001611808140221"}}},"execution_count":8,"outputs":[]},{"cell_type":"markdown","source":["拉取解析文章，创建检索器"],"metadata":{"id":"-r3nGKnNrdJI"}},{"cell_type":"code","source":["from langchain.text_splitter import RecursiveCharacterTextSplitter\n","from langchain_community.document_loaders import WebBaseLoader\n","from langchain_community.vectorstores import Chroma\n","from langchain_nomic.embeddings import NomicEmbeddings\n","urls = [\n","    \"https://lilianweng.github.io/posts/2023-06-23-agent/\",\n","    \"https://lilianweng.github.io/posts/2023-03-15-prompt-engineering/\",\n","    \"https://lilianweng.github.io/posts/2023-10-25-adv-attack-llm/\",\n","]\n","docs = [WebBaseLoader(url).load() for url in urls]\n","docs_list = [item for sublist in docs for item in sublist]\n","text_splitter = RecursiveCharacterTextSplitter.from_tiktoken_encoder(\n","    chunk_size=250, chunk_overlap=0)\n","doc_splits = text_splitter.split_documents(docs_list)\n","# Add to vectorDB\n","vectorstore = Chroma.from_documents(\n","    documents=doc_splits,\n","    collection_name=\"rag-chroma\",\n","    # 拉取量化模型到本地\n","    embedding=NomicEmbeddings(model=\"nomic-embed-text-v1.5\", inference_mode=\"local\"),\n",")\n","retriever = vectorstore.as_retriever()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"jtx5_yRzluBu","executionInfo":{"status":"ok","timestamp":1726987348886,"user_tz":-480,"elapsed":123347,"user":{"displayName":"李辉","userId":"12972001611808140221"}},"outputId":"42eea13e-bda4-4d2c-e753-0e75e0677a41"},"execution_count":9,"outputs":[{"output_type":"stream","name":"stderr","text":["WARNING:langchain_community.utils.user_agent:USER_AGENT environment variable not set, consider setting it to identify your requests.\n","Downloading: 100%|██████████| 274M/274M [00:03<00:00, 77.3MiB/s]\n","Verifying: 100%|██████████| 274M/274M [00:00<00:00, 526MiB/s]\n"]}]},{"cell_type":"code","source":["# Ollama model name\n","local_llm = \"mistral\""],"metadata":{"id":"KsS3tFrOnPn5","executionInfo":{"status":"ok","timestamp":1726987392730,"user_tz":-480,"elapsed":4,"user":{"displayName":"李辉","userId":"12972001611808140221"}}},"execution_count":10,"outputs":[]},{"cell_type":"markdown","source":["使用联网工具还是RAG检索路由节点"],"metadata":{"id":"R0HnQ9F2ut16"}},{"cell_type":"code","source":["### Router\n","from langchain.prompts import PromptTemplate\n","from langchain_community.chat_models import ChatOllama\n","from langchain_core.output_parsers import JsonOutputParser\n","# LLM\n","llm = ChatOllama(model=local_llm, format=\"json\", temperature=0)\n","prompt = PromptTemplate(\n","    template=\"\"\"You are an expert at routing a user question to a vectorstore or web search. \"\"\"\n","    \"\"\"Use the vectorstore for questions on LLM  agents, prompt engineering, and adversarial attacks. \"\"\"\n","    \"\"\"You do not need to be stringent with the keywords in the question related to these topics. \"\"\"\n","    \"\"\"Otherwise, use web-search. Give a binary choice 'web_search' or 'vectorstore' based on the question. \"\"\"\n","    \"\"\"Return the a JSON with a single key 'datasource' and no premable or explanation. \"\"\"\n","    \"\"\"Question to route: {question}\"\"\",\n","    input_variables=[\"question\"],\n",")\n","question_router = prompt | llm | JsonOutputParser()\n","question = \"llm agent memory\"\n","docs = retriever.get_relevant_documents(question)\n","doc_txt = docs[1].page_content\n","print(question_router.invoke({\"question\": question}))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"uGD1Jt3iltyB","executionInfo":{"status":"ok","timestamp":1726987637700,"user_tz":-480,"elapsed":6270,"user":{"displayName":"李辉","userId":"12972001611808140221"}},"outputId":"18026ed7-b42c-4f34-ec3d-6011c4ab7c16"},"execution_count":11,"outputs":[{"output_type":"stream","name":"stderr","text":["<ipython-input-11-75999d8d987c>:18: LangChainDeprecationWarning: The method `BaseRetriever.get_relevant_documents` was deprecated in langchain-core 0.1.46 and will be removed in 1.0. Use :meth:`~invoke` instead.\n","  docs = retriever.get_relevant_documents(question)\n"]},{"output_type":"stream","name":"stdout","text":["{'datasource': 'vectorstore'}\n"]}]},{"cell_type":"markdown","source":["文章片段评估节点"],"metadata":{"id":"8DVPH2MLu7bq"}},{"cell_type":"code","source":["### Retrieval Grader\n","\n","from langchain.prompts import PromptTemplate\n","from langchain_community.chat_models import ChatOllama\n","from langchain_core.output_parsers import JsonOutputParser\n","\n","# LLM\n","llm = ChatOllama(model=local_llm, format=\"json\", temperature=0)\n","\n","prompt = PromptTemplate(\n","    template=\"\"\"You are a grader assessing relevance of a retrieved document to a user question. \\n\n","    Here is the retrieved document: \\n\\n {document} \\n\\n\n","    Here is the user question: {question} \\n\n","    If the document contains keywords related to the user question, grade it as relevant. \\n\n","    It does not need to be a stringent test. The goal is to filter out erroneous retrievals. \\n\n","    Give a binary score 'yes' or 'no' score to indicate whether the document is relevant to the question. \\n\n","    Provide the binary score as a JSON with a single key 'score' and no premable or explanation.\"\"\",\n","    input_variables=[\"question\", \"document\"],\n",")\n","\n","retrieval_grader = prompt | llm | JsonOutputParser()\n","question = \"agent memory\"\n","docs = retriever.get_relevant_documents(question)\n","doc_txt = docs[1].page_content\n","print(retrieval_grader.invoke({\"question\": question, \"document\": doc_txt}))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"r_R-NWEynitG","executionInfo":{"status":"ok","timestamp":1726987888259,"user_tz":-480,"elapsed":1221,"user":{"displayName":"李辉","userId":"12972001611808140221"}},"outputId":"05787f10-53d1-448e-e29d-3c3d9e9b3abb"},"execution_count":12,"outputs":[{"output_type":"stream","name":"stdout","text":["{'score': 'yes'}\n"]}]},{"cell_type":"markdown","source":["根据文章片段生成答案节点"],"metadata":{"id":"ac-dG_ZovVT2"}},{"cell_type":"code","source":["### Generate\n","\n","from langchain import hub\n","from langchain_community.chat_models import ChatOllama\n","from langchain_core.output_parsers import StrOutputParser\n","\n","# Prompt\n","prompt = hub.pull(\"rlm/rag-prompt\")\n","\n","# LLM\n","llm = ChatOllama(model=local_llm, temperature=0)\n","\n","\n","# Post-processing\n","def format_docs(docs):\n","    return \"\\n\\n\".join(doc.page_content for doc in docs)\n","\n","\n","# Chain\n","rag_chain = prompt | llm | StrOutputParser()\n","\n","# Run\n","question = \"agent memory\"\n","generation = rag_chain.invoke({\"context\": docs, \"question\": question})\n","print(generation)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"vywU-0uinptJ","executionInfo":{"status":"ok","timestamp":1726987992260,"user_tz":-480,"elapsed":4372,"user":{"displayName":"李辉","userId":"12972001611808140221"}},"outputId":"7f6ee3e1-b243-4e72-f884-5907704a3825"},"execution_count":13,"outputs":[{"output_type":"stream","name":"stdout","text":["1. In an LLM-powered autonomous agent system, the memory stream serves as the long-term memory module, recording comprehensive experiences in natural language.\n","2. The design of generative agents combines LLM with memory, planning and reflection mechanisms to enable agents to behave conditioned on past experience.\n","3. Short-term memory in these agents utilizes in-context learning, while long-term memory provides the capability to retain and recall information over extended periods by leveraging an external vector store and fast retrieval.\n"]}]},{"cell_type":"markdown","source":["模型幻觉评估节点"],"metadata":{"id":"kQ7HHjBOvvMS"}},{"cell_type":"code","source":["### Hallucination Grader\n","\n","# LLM\n","llm = ChatOllama(model=local_llm, format=\"json\", temperature=0)\n","\n","# Prompt\n","prompt = PromptTemplate(\n","    template=\"\"\"You are a grader assessing whether an answer is grounded in / supported by a set of facts. \\n\n","    Here are the facts:\n","    \\n ------- \\n\n","    {documents}\n","    \\n ------- \\n\n","    Here is the answer: {generation}\n","    Give a binary score 'yes' or 'no' score to indicate whether the answer is grounded in / supported by a set of facts. \\n\n","    Provide the binary score as a JSON with a single key 'score' and no preamble or explanation.\"\"\",\n","    input_variables=[\"generation\", \"documents\"],\n",")\n","\n","hallucination_grader = prompt | llm | JsonOutputParser()\n","hallucination_grader.invoke({\"documents\": docs, \"generation\": generation})"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"_QVlbdFJn_G9","executionInfo":{"status":"ok","timestamp":1726988143320,"user_tz":-480,"elapsed":657,"user":{"displayName":"李辉","userId":"12972001611808140221"}},"outputId":"a07ad79f-3f1d-40e1-aae7-229af517ed24"},"execution_count":16,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'score': 'yes'}"]},"metadata":{},"execution_count":16}]},{"cell_type":"markdown","source":["生成答案评估节点"],"metadata":{"id":"B9L18OqFwBZw"}},{"cell_type":"code","source":["### Answer Grader\n","\n","# LLM\n","llm = ChatOllama(model=local_llm, format=\"json\", temperature=0)\n","\n","# Prompt\n","prompt = PromptTemplate(\n","    template=\"\"\"You are a grader assessing whether an answer is useful to resolve a question. \\n\n","    Here is the answer:\n","    \\n ------- \\n\n","    {generation}\n","    \\n ------- \\n\n","    Here is the question: {question}\n","    Give a binary score 'yes' or 'no' to indicate whether the answer is useful to resolve a question. \\n\n","    Provide the binary score as a JSON with a single key 'score' and no preamble or explanation.\"\"\",\n","    input_variables=[\"generation\", \"question\"],\n",")\n","\n","answer_grader = prompt | llm | JsonOutputParser()\n","answer_grader.invoke({\"question\": question, \"generation\": generation})"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"vUhBgC0_oK1i","executionInfo":{"status":"ok","timestamp":1726988212967,"user_tz":-480,"elapsed":1393,"user":{"displayName":"李辉","userId":"12972001611808140221"}},"outputId":"12258830-4e47-4af9-b472-ad328e2cc3af"},"execution_count":17,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'score': 'yes'}"]},"metadata":{},"execution_count":17}]},{"cell_type":"markdown","source":["问题重写节点"],"metadata":{"id":"ey1405BrwIwo"}},{"cell_type":"code","source":["### Question Re-writer\n","\n","# LLM\n","llm = ChatOllama(model=local_llm, temperature=0)\n","\n","# Prompt\n","re_write_prompt = PromptTemplate(\n","    template=\"\"\"You a question re-writer that converts an input question to a better version that is optimized \\n\n","     for vectorstore retrieval. Look at the initial and formulate an improved question. \\n\n","     Here is the initial question: \\n\\n {question}. Improved question with no preamble: \\n \"\"\",\n","    input_variables=[\"generation\", \"question\"],\n",")\n","\n","question_rewriter = re_write_prompt | llm | StrOutputParser()\n","question_rewriter.invoke({\"question\": question})"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"_Fi-RivBoKl0","executionInfo":{"status":"ok","timestamp":1726988340325,"user_tz":-480,"elapsed":1275,"user":{"displayName":"李辉","userId":"12972001611808140221"}},"outputId":"7c2e12fe-51bc-46bd-b5d6-4a485849fb9c"},"execution_count":18,"outputs":[{"output_type":"execute_result","data":{"text/plain":["\" What is the function of an agent's memory in a given context?\""],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":18}]},{"cell_type":"markdown","source":["联网查询工具"],"metadata":{"id":"RMOLP_A7wMIA"}},{"cell_type":"code","source":["### Search\n","\n","from langchain_community.tools.tavily_search import TavilySearchResults\n","\n","web_search_tool = TavilySearchResults(k=3)"],"metadata":{"id":"sXouDU_WoXyi","executionInfo":{"status":"ok","timestamp":1726988399065,"user_tz":-480,"elapsed":1379,"user":{"displayName":"李辉","userId":"12972001611808140221"}}},"execution_count":20,"outputs":[]},{"cell_type":"markdown","source":["# 构建graph工作流"],"metadata":{"id":"C597e0BLwTrI"}},{"cell_type":"code","source":["from typing import List\n","\n","from typing_extensions import TypedDict\n","\n","\n","class GraphState(TypedDict):\n","    \"\"\"\n","    Represents the state of our graph.\n","\n","    Attributes:\n","        question: question\n","        generation: LLM generation\n","        documents: list of documents\n","    \"\"\"\n","\n","    question: str\n","    generation: str\n","    documents: List[str]"],"metadata":{"id":"vec7W3aDovWZ","executionInfo":{"status":"ok","timestamp":1726988444909,"user_tz":-480,"elapsed":1449,"user":{"displayName":"李辉","userId":"12972001611808140221"}}},"execution_count":21,"outputs":[]},{"cell_type":"markdown","source":["定义封装节点"],"metadata":{"id":"1y5LPpWvwfRL"}},{"cell_type":"code","source":["### Nodes\n","\n","from langchain.schema import Document\n","\n","### 检索器\n","def retrieve(state):\n","    \"\"\"\n","    Retrieve documents\n","\n","    Args:\n","        state (dict): The current graph state\n","\n","    Returns:\n","        state (dict): New key added to state, documents, that contains retrieved documents\n","    \"\"\"\n","    print(\"---RETRIEVE---\")\n","    question = state[\"question\"]\n","\n","    # Retrieval\n","    documents = retriever.get_relevant_documents(question)\n","    return {\"documents\": documents, \"question\": question}\n","\n","### 生成答案\n","def generate(state):\n","    \"\"\"\n","    Generate answer\n","\n","    Args:\n","        state (dict): The current graph state\n","\n","    Returns:\n","        state (dict): New key added to state, generation, that contains LLM generation\n","    \"\"\"\n","    print(\"---GENERATE---\")\n","    question = state[\"question\"]\n","    documents = state[\"documents\"]\n","\n","    # RAG generation\n","    generation = rag_chain.invoke({\"context\": documents, \"question\": question})\n","    return {\"documents\": documents, \"question\": question, \"generation\": generation}\n","\n","### 文章片段相关性评估\n","def grade_documents(state):\n","    \"\"\"\n","    Determines whether the retrieved documents are relevant to the question.\n","\n","    Args:\n","        state (dict): The current graph state\n","\n","    Returns:\n","        state (dict): Updates documents key with only filtered relevant documents\n","    \"\"\"\n","\n","    print(\"---CHECK DOCUMENT RELEVANCE TO QUESTION---\")\n","    question = state[\"question\"]\n","    documents = state[\"documents\"]\n","\n","    # Score each doc\n","    filtered_docs = []\n","    for d in documents:\n","        score = retrieval_grader.invoke(\n","            {\"question\": question, \"document\": d.page_content}\n","        )\n","        grade = score[\"score\"]\n","        if grade == \"yes\":\n","            print(\"---GRADE: DOCUMENT RELEVANT---\")\n","            filtered_docs.append(d)\n","        else:\n","            print(\"---GRADE: DOCUMENT NOT RELEVANT---\")\n","            continue\n","    return {\"documents\": filtered_docs, \"question\": question}\n","\n","### 重新表述问题\n","def transform_query(state):\n","    \"\"\"\n","    Transform the query to produce a better question.\n","\n","    Args:\n","        state (dict): The current graph state\n","\n","    Returns:\n","        state (dict): Updates question key with a re-phrased question\n","    \"\"\"\n","\n","    print(\"---TRANSFORM QUERY---\")\n","    question = state[\"question\"]\n","    documents = state[\"documents\"]\n","\n","    # Re-write question\n","    better_question = question_rewriter.invoke({\"question\": question})\n","    return {\"documents\": documents, \"question\": better_question}\n","\n","### 联网查询\n","def web_search(state):\n","    \"\"\"\n","    Web search based on the re-phrased question.\n","\n","    Args:\n","        state (dict): The current graph state\n","\n","    Returns:\n","        state (dict): Updates documents key with appended web results\n","    \"\"\"\n","\n","    print(\"---WEB SEARCH---\")\n","    question = state[\"question\"]\n","\n","    # Web search\n","    docs = web_search_tool.invoke({\"query\": question})\n","    web_results = \"\\n\".join([d[\"content\"] for d in docs])\n","    web_results = Document(page_content=web_results)\n","\n","    return {\"documents\": web_results, \"question\": question}\n","\n","\n","### Edges ###\n","\n","### web search 或 RAG 路由\n","def route_question(state):\n","    \"\"\"\n","    Route question to web search or RAG.\n","\n","    Args:\n","        state (dict): The current graph state\n","\n","    Returns:\n","        str: Next node to call\n","    \"\"\"\n","\n","    print(\"---ROUTE QUESTION---\")\n","    question = state[\"question\"]\n","    print(question)\n","    source = question_router.invoke({\"question\": question})\n","    print(source)\n","    print(source[\"datasource\"])\n","    if source[\"datasource\"] == \"web_search\":\n","        print(\"---ROUTE QUESTION TO WEB SEARCH---\")\n","        return \"web_search\"\n","    elif source[\"datasource\"] == \"vectorstore\":\n","        print(\"---ROUTE QUESTION TO RAG---\")\n","        return \"vectorstore\"\n","\n","### 生成回答或重写问题路由\n","def decide_to_generate(state):\n","    \"\"\"\n","    Determines whether to generate an answer, or re-generate a question.\n","\n","    Args:\n","        state (dict): The current graph state\n","\n","    Returns:\n","        str: Binary decision for next node to call\n","    \"\"\"\n","\n","    print(\"---ASSESS GRADED DOCUMENTS---\")\n","    state[\"question\"]\n","    filtered_documents = state[\"documents\"]\n","\n","    if not filtered_documents:\n","        # All documents have been filtered check_relevance\n","        # We will re-generate a new query\n","        print(\n","            \"---DECISION: ALL DOCUMENTS ARE NOT RELEVANT TO QUESTION, TRANSFORM QUERY---\"\n","        )\n","        return \"transform_query\"\n","    else:\n","        # We have relevant documents, so generate answer\n","        print(\"---DECISION: GENERATE---\")\n","        return \"generate\"\n","\n","### 采用答案或重新回答\n","def grade_generation_v_documents_and_question(state):\n","    \"\"\"\n","    Determines whether the generation is grounded in the document and answers question.\n","\n","    Args:\n","        state (dict): The current graph state\n","\n","    Returns:\n","        str: Decision for next node to call\n","    \"\"\"\n","\n","    print(\"---CHECK HALLUCINATIONS---\")\n","    question = state[\"question\"]\n","    documents = state[\"documents\"]\n","    generation = state[\"generation\"]\n","\n","    score = hallucination_grader.invoke(\n","        {\"documents\": documents, \"generation\": generation}\n","    )\n","    grade = score[\"score\"]\n","\n","    # Check hallucination\n","    if grade == \"yes\":\n","        print(\"---DECISION: GENERATION IS GROUNDED IN DOCUMENTS---\")\n","        # Check question-answering\n","        print(\"---GRADE GENERATION vs QUESTION---\")\n","        score = answer_grader.invoke({\"question\": question, \"generation\": generation})\n","        grade = score[\"score\"]\n","        if grade == \"yes\":\n","            print(\"---DECISION: GENERATION ADDRESSES QUESTION---\")\n","            return \"useful\"\n","        else:\n","            print(\"---DECISION: GENERATION DOES NOT ADDRESS QUESTION---\")\n","            return \"not useful\"\n","    else:\n","        pprint(\"---DECISION: GENERATION IS NOT GROUNDED IN DOCUMENTS, RE-TRY---\")\n","        return \"not supported\""],"metadata":{"id":"qYmJ6DeBow8E","executionInfo":{"status":"ok","timestamp":1726988874182,"user_tz":-480,"elapsed":1121,"user":{"displayName":"李辉","userId":"12972001611808140221"}}},"execution_count":23,"outputs":[]},{"cell_type":"code","source":["from langgraph.graph import END, StateGraph, START\n","\n","workflow = StateGraph(GraphState)\n","\n","# Define the nodes\n","workflow.add_node(\"web_search\", web_search)  # web search\n","workflow.add_node(\"retrieve\", retrieve)  # retrieve\n","workflow.add_node(\"grade_documents\", grade_documents)  # grade documents\n","workflow.add_node(\"generate\", generate)  # generatae\n","workflow.add_node(\"transform_query\", transform_query)  # transform_query\n","\n","# Build graph\n","workflow.add_conditional_edges(\n","    START,\n","    route_question,\n","    {\n","        \"web_search\": \"web_search\",\n","        \"vectorstore\": \"retrieve\",\n","    },\n",")\n","workflow.add_edge(\"web_search\", \"generate\")\n","workflow.add_edge(\"retrieve\", \"grade_documents\")\n","workflow.add_conditional_edges(\n","    \"grade_documents\",\n","    decide_to_generate,\n","    {\n","        \"transform_query\": \"transform_query\",\n","        \"generate\": \"generate\",\n","    },\n",")\n","workflow.add_edge(\"transform_query\", \"retrieve\")\n","workflow.add_conditional_edges(\n","    \"generate\",\n","    grade_generation_v_documents_and_question,\n","    {\n","        \"not supported\": \"generate\",\n","        \"useful\": END,\n","        \"not useful\": \"transform_query\",\n","    },\n",")\n","\n","# Compile\n","app = workflow.compile()"],"metadata":{"id":"Gn3FoJrFo2a7","executionInfo":{"status":"ok","timestamp":1726989033322,"user_tz":-480,"elapsed":737,"user":{"displayName":"李辉","userId":"12972001611808140221"}}},"execution_count":24,"outputs":[]},{"cell_type":"code","source":["from IPython.display import Image, display\n","display(Image(app.get_graph(xray=True).draw_mermaid_png()))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":611},"id":"GcI36If6pxYn","executionInfo":{"status":"ok","timestamp":1726989044894,"user_tz":-480,"elapsed":1883,"user":{"displayName":"李辉","userId":"12972001611808140221"}},"outputId":"f6310fa0-7e4e-4208-d509-ab1621e89852"},"execution_count":25,"outputs":[{"output_type":"display_data","data":{"image/jpeg":"/9j/4AAQSkZJRgABAQAAAQABAAD/4gHYSUNDX1BST0ZJTEUAAQEAAAHIAAAAAAQwAABtbnRyUkdCIFhZWiAH4AABAAEAAAAAAABhY3NwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQAA9tYAAQAAAADTLQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlkZXNjAAAA8AAAACRyWFlaAAABFAAAABRnWFlaAAABKAAAABRiWFlaAAABPAAAABR3dHB0AAABUAAAABRyVFJDAAABZAAAAChnVFJDAAABZAAAAChiVFJDAAABZAAAAChjcHJ0AAABjAAAADxtbHVjAAAAAAAAAAEAAAAMZW5VUwAAAAgAAAAcAHMAUgBHAEJYWVogAAAAAAAAb6IAADj1AAADkFhZWiAAAAAAAABimQAAt4UAABjaWFlaIAAAAAAAACSgAAAPhAAAts9YWVogAAAAAAAA9tYAAQAAAADTLXBhcmEAAAAAAAQAAAACZmYAAPKnAAANWQAAE9AAAApbAAAAAAAAAABtbHVjAAAAAAAAAAEAAAAMZW5VUwAAACAAAAAcAEcAbwBvAGcAbABlACAASQBuAGMALgAgADIAMAAxADb/2wBDAAMCAgMCAgMDAwMEAwMEBQgFBQQEBQoHBwYIDAoMDAsKCwsNDhIQDQ4RDgsLEBYQERMUFRUVDA8XGBYUGBIUFRT/2wBDAQMEBAUEBQkFBQkUDQsNFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBT/wAARCAJSAikDASIAAhEBAxEB/8QAHQABAQADAQEBAQEAAAAAAAAAAAYEBQcIAwIBCf/EAF0QAAEEAQIEAQQKCRAIBQMFAQEAAgMEBQYRBxITITEUFSJBCBYXMkJRVmGRlCNTVFVik9HS0yUzNDU2N1JjZHF1gaOz1OEkQ3N0obG0wXKSlbLDCSaCRVdloqTw/8QAGwEBAQADAQEBAAAAAAAAAAAAAAECAwQFBgf/xAA4EQEAAQIBCQUGBQUBAQAAAAAAAQIRAxIUIVFSYZGh0QQxQWJxEyMzscHSBTJCkvAVIoHC4bLx/9oADAMBAAIRAxEAPwD/AFTREQEREBERAREQEREBERAREQEREBERAREQEREBERARFps5mZ6s0OPx0LbOVsgljZN+nAweMshHflHgGju47AbDmc3Kmma5tB3tvJI2Jhe9wYwdy5x2AWtdqjDMcWuy9FpHiDZZ+Va5mgsbaeJsyHaht7k9TIgPjbv6mRbcjQPVsN/jJPdbBulMIxoa3D0GtHYAVWbD/gt1sGO+Zn+fzUug9tWE+/FD60z8qe2rCffih9aZ+Vf32rYX70UPqzPyJ7VsL96KH1Zn5E9zv5Lofz21YT78UPrTPyp7asJ9+KH1pn5V/fathfvRQ+rM/IntWwv3oofVmfkT3O/kaH89tWE+/FD60z8qe2rCffih9aZ+Vf32rYX70UPqzPyJ7VsL96KH1Zn5E9zv5Gh9qmcx1+TkrZCrYf8AwYpmuP0ArOWltaJ09dZyWMFjZm7bDnqRnb+bt2WDJh7mlGmzh32b1FgBkxE0nUIaPEwPd6Qd+A5xadthyb7pkYdWiidO/r/PVNCoRY9C/XylKG3VkEteZocx4BG4/mPcH4we49ayFomJibSgiIoCIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICmNE7ZLzrm37OmvW5IWO77iCF7oo2/zbh7/AOeQqnUxw9b5NgZqDtxLRu2a7wRt/rXOYf62OYf610U6MKqY79HDT9bL4KdFptUaz0/oehHe1Hncbp+lJKIWWcpcjrRvkIJDA55ALtmuO3jsD8SmR7IPha4OI4laQIaNyRnqvYeH2z51zo3fEXX+J4XaLymqM26YY3Hsa6QVo+pK8ue1jGMb63Oe5rR4Dc9yB3XLOJ3sh85pnQuEzmL0JqGpcualo4afH5apAycRySxh5YPKAwl7X8jHBxbz++2AJFDq3ifobiJpbLYDT97S3E3I265aNLV85UL70e46gHpOA2bu7cjxaO48Rymvwk4jzcJclVbi7EbsZqvH53TelsxmGW7MNStLDI6q63zOaOZzJOQF7g0FoLviDtOqOL1jS+JxFx3D/WWTnvwPnko4yjDPNSDdt2zkTcgd6XZrHuLtjtvsVpsj7JnTELND+acbm9TSazoz38PDiKrHPlbCIy9j+o9nTdtL8LZo5HbkEDeM4kaS1fxB1dprPZvhtNqXTwxU8DtH3MzWZHQyBn9GzYHOY5mmIAAt6hZudmklYPBLg3rHR1/gwzMYVlSPSmIzuOyM0VqKSNj5p4DXczZ3M5sjWOI9Hdu2zg0oLHSXHTP5/jtqHRtjRWYr4mnRx08dgx1g6m6dsznvsnyg7tPI1jRG1xBY/cbbE9sXFb+P1Hw+4+6g1bHgmZTSGoMXj697K+cIKwxHkr5+pLM2VzS6Ppzc+7Nz6BBHrVXH7ILhdK9rGcSdIPe4gNa3O1SSfiH2RBfooBnsguFsr2sZxJ0g97js1rc7VJJ+IfZFfoJjT+2L1XncQzZtd4jycLBv6JmdIJR/XJG55+eQqnUxj2+V8Q8xYbv06tGtUJI7dQukkcN/Xs10Z/8AyVOujH/NE7o+ULIiIudBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBTmUqz4HLy5unA+1Xna1mRqwtLpCGghk0bR75zQdnNHdzQOXdzGsfRE7Dc9gp2bVpydd403XjzU8lM2atoyFmPkPPyNYbDWvG5IcTyNeQGkkd2750V5E7lbapboZ6myxXlgv1XH0XsIe3cdj/WPD5l9PNtT7lh/Fj8imBw6hsZq/lrOQuRW7bYgI8dJ5KyEtZs9wMYDpS8nc9UvADWBobsScg6Im8G6ozzQPV5REf8AiY91tycKe6q3rHT/AIuhRRUq8L+eOCKN38JrACvspb2kT/KnPfj4v0Se0if5U578fF+iT2eHt8pLRrVKKW9pE/ypz34+L9EntIn+VOe/Hxfok9nh7fKS0a1Q5oe0tcAWkbEH1rH821PuWH8WPyKf9pE/ypz34+L9EntIn+VOe/Hxfok9nh7fKS0a1AMbUB/YsP4sfkWvzWo20ZfIKLG381I3eKk1+3Lv4SSnv04x63Eb9tmhziGnA9ook2FnP521HtsWG8Ytx/PEGH6CtziMFQwNd0NCrHWY48zy0buefDdzj3cfnJJS2FRpvlco6/zvTRD56fwrcHQMJl8osyyOns2C3lM0rju52252HqA3OzQ0b9ls1rMjh5rmSp3YcnbpOrMlYa8RaYJ+doAMrC0k8pAcC0tO+43IJB11fI6gxMVePK0YMq2OlJLayOKaYuaZh7MZVe5zgHt8NpHkHsfU46aqpqmap70UiLVYvVOLzFiOrXuMF99SO8cfODDbjgk35HyQPAkjBII9Jo2LXA9wQtqsQREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQERajM6kgxTpqsEZyWYFV9uHE1pIxYnY1zW7tD3NaBzOaOZxDRv3IQbdaEauhv2BFhYDnOlkDj7stSaMR0XNbzSGQucN+XcN5WBzuZwBAAcW/ifTtnPusNzlhsuPkdXlhxtbniELo/ScJJGu3mDn+IIa0ta0Fp9IuoAA0bAAevsgnqembV2Whcz183b1XrgQUjJXpuEhIAfDzu6paz0d3kjfmcGtJAG/hhjrQxwwxtiijaGMjYAGtaBsAAPABftEBERAREQEREBERAREQEREGvzOAx+oKU9XIVWWIZ4nQP33a7kJBIDhs5vcA7gg7gHxAWst4nN4uO7NhciLsjmV2Vsdl37wRch2kIma0y7vb4ueZNnAHbuQaNEGhk1jToWZ4ssx+DY25HRr2Mg5jIbj5B9j6Tw4g8x9ENds7m7bd2775fmSNsrC17Q9p8WuG4K0cGm5sRbifiLrq1WS7Lbu1bRfYbN1Bu4Rlz94dn7OAbu3u8cvpbtDfItJhNURZJ9aldh80Z2WsbT8RYlY6ZjA/kc5paSHtDtvSb4c7N9i4BbtAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREGpuZouyzcXj3VLN+IRT3IJbBY+vWeXtbLyhriS50bw0HlDuR/peiV9MDgodP4+KtHNYuSNbtJcuymWeY8znEvefwnuIaNmt32aGgADW6Hux5Wlk70eTiyzZMpcg60VTyfpdCd8BgI8XmN0TmF598Wkj0SFSICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiDBzGIhzWPsVZXzQdWN0YsVpDHNFvt6THju0ggHf4wFhwZmWhkhQy7q8DrM5jxszJD/pbRGHlrgWgMlG0noAu5ms5wffNZuljZGn5xoWKvXmqmaNzBPWfyyR7jbmafUR4jsUGSi1en7tizXngt17cVinMazprTWDykAAiZpZ6Ja4EHsBseYbDbZbRAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERARFGP1fl8sDPg8fSfjyT0rV+w9hnH8JrGsOzD32JO52322IK24eFViflWIus0UR581h9w4P61N+jTz5rD7hwf1qb9Gt+a1644wWW6KI8+aw+4cH9am/Rp581h9w4P61N+jTNa9ccYLLdc+48cTshwc4Z5TV9DTrtUNxnLJZost+TvbBvs6Rp5H78u4JGw7bnft3yvPmsPuHB/Wpv0ax8lb1PmMdaoXcXgLNO1E+CeCSxMWyRuBa5pHT8CCQma1644wWcR9hz7MTIeyN1Dm8FY0pLQjoR2ci/Liy10bWyWt69YsbG0czYpOXn33d0HOI3cdvVq84+x34H3/Y4aayeJwVfE3HZC6+3PbszyCRzfCOM7R9wxvYfOXHtvsOr+fNYfcOD+tTfo0zWvXHGCy3RRHnzWH3Dg/rU36NPPmsPuHB/Wpv0aZrXrjjBZboojz5rD7hwf1qb9GnnzWH3Dg/rU36NM1r1xxgst0UUzO6ua4F+Pwr2jxa25M0n+vpHb6CqLAZ2LP0nTMjfXmieYbFaX38MgAJadux7EEEdiCCOxWuvArw4yp7t03LNmiIudBERAREQEREBERAREQEREBERBO5Okcfq3GZarjRYluDzdet+WdLoQBskkTjGfRk+y+gNvSHWJG45lRKd4gUPL9IZHkx1fLWarWX6tO1P0I5LED2zQ7yfA2kjYQ7wBAJ7KgY8SMa5pDmuG4IO4IQfpERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREGNkiW460QSCInkEfzFRWhgBorT4AAHm+v2A2A+xtVpk/wBrbf8AsX/+0qL0P+4rT/8AR9f+7avQwPhVesfKV8G7REWaCItPqHV2J0rLiI8pb8lflrzMbSHTe/q2Hte9rPRB5d2xvO7th28e4UG4REVBERAREQEWnyOrsTitSYfAWrfSy2XjnlpV+m89VsIYZTzAcreUSM98Rvv232K3CgLB0If1e1gPV5fCe3x+SQ/5fQs5YGhP2/1h/v8AD/0sKyn4Vfp9YZR3SskRF5bEREQEREBERAREQEREBERAREQY2SpR5HHWqk0TLEM8T4nxSe9e1wILT8xB2Wu0UZXaOwRmrV6U3kEHUrVJutDC7pt3YyT4bQewd6wAVulO8Oqnm/QmBq+QVMUIKcUQpUJutBAGtADI3/CaANgUFEiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiDFyf7W2/wDYv/8AaVF6H/cVp/8Ao+v/AHbVaZP9rbf+xf8A+0qL0P8AuK0//R9f+7avQwPg1esfKV8G4nhFiCSIuewPaWl0bi1w3G24I7g/OF46wXGrWeBfhKd27atUOGU8lTXNywXyPuRPsuq15S7xeWwg2nHuTsD4r2QtDNoTATwakhkxcDo9R7+dmkH/AEveFsB5u/2tjW9tvWfEkmzEz3I8su1Xr/U1Ph1jILt5svEGfLakkgkzsuMkbXbyOqU4bLYpXxNbA9jyxjQSQe43dvnaw0XravhtCYPWWVnigscQqnmyenmX3L1Wu6lZ5o3W3QxOc4PDy1xbzAOA5iQCvRer+Feldd4Cjhc3h4rePoOY+m1j3wyVXMHK10UkbmvjIHbdrh2Wrs8BdCXNKUdNz4Lq4eldORghfbnL22S17esZefnc/aR/pFxIJBHcAjDJkS3B6xlNNcWde6Dlz2S1LhMXVoZGnZy9g2bVR1gSh9d8x9J4+xB7ebuA7xKseNWF1RqDhnmaGjb5x2oZWxmCZk/Qe5okaZI2S7HpuewPYH7eiXA9vEYlDhaeHuEdR4bNxGnpbFk2Ls+Yq2Mk+yeXbdz/AChkjndh3c92wG2y/Mug9R6yo28Pr/IafzunbLG89TE421Qm6rXtfG7q+VvIDS3fsAdwDuNu+VptYcGynETLXcPpHRGlLWpKd/Jait4zMwalzroL9SaGqJvI23wyYta/djmvYHFw3Ac3m7UVyHWvD3Q+bxmrbuYlhzeVoY/TNPC6lfayYsSb9SF9+WCJzI3cgdzOBc1pfsd+VdbHALQHtNl0s7TkMmGlt+cHslnlfM6z2+z9cvMvV2AHPz82w232X6j4E6Hj0fY0x5kL8RPbbfkbJcsPnNlvLyzCcyGUSDkaA4P3AG26xyZHm/Jam13geHHFLTNnPZTF5PC6gwMNC354fkLdOO3NVL4/KnMjdK30ndnt8Hlp5h49M1TgbkHFDR/DOvqzUuNwWRpX81cvHLyuv3pYjCxteOw4l8bBzukLYy0du3KFe1PY9cP6NLIVYMB04ci+rLcAuWC6zJXm60MkjjJu57X9y8kud4OJHZb3XnDLTPE2nUrakxbb7akvXrTMmkgnrv22Lo5Y3NewkdjyuG/rVyZHGOInDhruLfBrTI1NqMQMp58vyXnJ3nCRnLWdyGxtzgdwOYEO2aBzeJNz7HXL5O7prUuLymTtZl+n9SZDD1719/UsSwRSAx9V/wANwa7lLj3Ow3VNguEek9Nz4CfHYowTYJtpuPebMzzF5SWmcnmeecvLQSX8x38CNytxpzSOJ0kMmMTU8kGSvS5K39ke/qWJdjI/0idt9h2GwHqAViLTcbhYGhP2/wBYf7/D/wBLCs9YGhP2/wBYf7/D/wBLCtk/Cr9PrDKO6VkiIvLYiIiAiIgIiICIiAiIgIiICIiAp7h7TFDROGrChVxYirtaKdKbqww/gsfueYfOqFTvDun5BojDV/N9XFdOu1vkVGbrQw/gsf8ACHzoKJERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREGLk/wBrbf8AsX/+0qL0P+4rT/8AR9f+7ar1zQ9pa4BzSNiD4EKAr47N6TqRYyDDy5ulVYIqtitZibIYhsGNkbK5vpgdiQSHbc3YnlHf2eYmiqi9pvE6Ztr1so0xZvUWk87Z/wCRuT+tU/06eds/8jcn9ap/p10ez80fup6lm7RaTztn/kbk/rVP9OnnbP8AyNyf1qn+nT2fmj91PUs3aLSeds/8jcn9ap/p087Z/wCRuT+tU/06ez80fup6lm7RSWA1vkNUUJbmN0plLFaO1ZpOf16rNpq874Jm7OmB9GSJ7d/A7bjcEFbLztn/AJG5P61T/Tp7PzR+6nqWbtFpPO2f+RuT+tU/06eds/8AI3J/Wqf6dPZ+aP3U9SzdotJ52z/yNyf1qn+nTztn/kbk/rVP9Ons/NH7qepZu1gaE/b/AFh/v8P/AEsKxWZLUEh5RpC/GfU6W3UDf6+WUn/gqDSmCmw1a3NceyTIX5/KbPSJMbHcjWNYwnuWtaxo32HMeZ2zebYYYkxRh1RMxp0aJifGJ8PQ7obxEReWxEREBERAREQEREBERAREQEREBTvDun5BojDV/N9XFdOu1vkVGbrQw/gsf8IfOqJTvDun5BojDV/N9XFdOu1vkVGbrQw/gsf8IfOgokREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREEFwUby6NyA5eX/AO48+duXl/8A1e58w+nbv8Z8Tern/A5gj0VkAGub/wDcuoDs5vKe+ZuHfxPb5/X49vBdAQEREBERAREQEREBERAREQEREBERAREQEREBERAU7w7p+QaIw1fzfVxXTrtb5FRm60MP4LH/AAh86olO8O6fkGiMNX831cV067W+RUZutDD+Cx/wh86CiREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQc94FlrtE5EtO49s2ofFob3883d+w/5+vxXQlAcEA8aLyHUMjne2XUHeUbHbzxc2/q222+bZX6AiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICnOHdTyDRGGr+QVcX067W+R0ZutDD+Cx/wAIfOqNTnDur5DofCwCjTxojrtb5Jj5utBF+Cx/wh86CjREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEWHlczQwVUWcjdr0K5cGCWzK2NpcfBoJPcn4lovdU0d8qMT9cj/ACrbTg4lcXopmf8AC2mVSilvdU0d8qMT9cj/ACp7qmjvlRifrkf5Vnm2NsTwlcmdSpWp1Lq3B6Mx7b+oMzj8FRdIIhayVpleIvIJDeZ5A3IB7fMVrPdU0d8qMT9cj/KojjU7h/xm4X6g0hkNUYZrMjWcyGZ1th6E49KKTx39F4aTt4jcetM2xtieEmTOp/fY66/0rqHT+SxeG1JiMnkW5zPXXUqV6KWYQvy9pzZSxr3HkcJGEO8CHtPbcBdfXgH/AOnXw1w/CGPVGq9XZXH4vUNuR2Jq1rFpjXtrMe10j9t+7ZHtZsfWI9+4IXtX3VNHfKjE/XI/ypm2NsTwkyZ1KlFLe6po75UYn65H+VPdU0d8qMT9cj/KmbY2xPCTJnUqUUt7qmjvlRifrkf5Vm4nXGnc9abWx2cx96y7cthgsse92w3OwB3Ow8fiUnAxaYvNE29JS0t4iItCCIiAiIgIiICIiAiIgIiICIiAiIgKd4d1fItEYaDyKljunXa3yTHS9WvF+Cx/wh86olO8PKpo6Iw0BoU8WY67W+R0JerBF+Cx/wAIfOgokREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREEHByZTWuobNgCWbHTx0axeN+jGa8MzuX4i50vpEbE8rQdw1u25Wkw37q9a/0pF/0NVbtevXoyY3U/KGUiIi1sRERAREQEREBYWZxVfM46WtYZu0jdjx2dG8d2vYR3a5pAIcCCCAQQVmr8ye8d/MVaZmmYmBmaLysud0dgslOeae5QgsSHlA3c+Nrj2Hh3K3KmOF372ekf6Iqf3LFTrhxoinFqiNcrPeIiLSgiIgIiICIiAiIgIi1mSzPm6dsfR6m7ebfm29Z+b5kGzRaH20fyb+0/yT20fyb+0/yQb5FofbR/Jv7T/JPbR/Jv7T/JBvlOcOqzamh8LC2rRpNZXaBXxk3VrR/NG/4TfnX19tH8m/tP8lrdNZGPAYGjjoaNWCKtEI2x0gYoWgepjTzbD5tygsEWh9tH8m/tP8k9tH8m/tP8kG+RaH20fyb+0/yT20fyb+0/yQb5Fpa+o+vPHH5Py87g3fn8Nz/Mt0gIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiIIHDfur1r/SkX/Q1Vu1pMN+6vWv8ASkX/AENVbtevifp9Kf8AzDKrvcY4meyAymkMlrCtp7RrtTwaQx8eQzdmTJNqCBr43StZE0scZXCNpe73oA22JJ2Wn1b7LLH4HLQYmjWwNnJRY6tkL4y2pq+Kij68fUZFAZm80zuXY+9Y0BzdyCdhzP2TU9HB8W85NNksQyvk8RWjv6fmyuQxsuZYwybRvEVaRlgkHkHI9pAPK4EFdNx+gtaQ6im15ovHYGnHq/FY+XJad1U2WJ+NsRQBjOm6Jjt9mEMdGQ3vGNnDwHLeZnQxZ2K9kjb1vkMBT0RpLz7JmcB5/ifeybaTIWCYwvikIZJ6QcAAWhwJPqA5lh5b2W+FqaP0fkq9KnBl9SR2JI6GczEGNr1fJ5OlP1bL9x2kHK0Na4u7kAAHa2xfD3MQcYaGsLc2PNaPSww08VUPYTaNhsrnMYQQI+x23dv4dj4rm2D9jxq7RmM0ZlcJdwNjVeBOVrWKeRMpoXadu4+wG9QM52PZuwghhG/MO42Jy/uGfV9llDl9M4a7htNNzWVvam9q01GlloZYY7BrvmbLHYYCyWIgM9L0dg5xI3bynd8S+N+peF+Ex9/K6SwkZkgfLabY1ZBWY17XO+w1zLE0zvLQ123Kwbu23WZmOHeq9VwcO7WWdgauTwWo/PF+PG9VkBhEFiJrIuZpL3jqx7l3KDs49uwWu4h8IdTZribf1LhDp65DlMIzCvdn2yvlxYD5C6Wu1jSH84kHMwuZuWN9Lbsn91hqdU8ZNXZbX3CKXRGNq5DTuqcPbynkt/IeSOsfYontEhEEhZ02yAjYnmLyCByAn+cQPZd4nR+qM/i6VTD34dPv6WQdkNSVcdZklDA97KteTd0xaHAbksBdu0EkFfunwX1vpzTfCKfEWcBPqXQ1GfFzV7s07aduCSJkXO2RsZe14EMbtuTbcuG/YE5dbhbxB0TqnU9vST9J3cVqS751sRZ5s/Ux9x8bGTGLptPWjcWBwa4xkHfup/cOxacz9PVWnsXm8e90lDJVYrld7hsXRyMD2kj1dnBZ8nvHfzFGNDGNaAGgDYBo2A/mST3jv5itsD88Lv3s9I/0RU/uWKnUxwu/ez0j/RFT+5YqdcfaPjV+s/NZ75ERFoQREQEREBERAREQFNam/ZzNvHpD/mVSqa1L+zo/9mP+ZQcNxvHt2S05gZm4Dl1LkdRP03Ng/LNzVnikf13mTp+kxkUbpd+QbgtHbfdSGU9mfp/H5G5OyviptN1LppS2TqGszJO5ZOm+VlA+m6MO3I3cHFo5g3bbe8xPBaLGcc8rrzysOpWagMGN+DDee1sdixttsC6GCu3fx/XPDfvotBcLtccM7DdPYl+l8hopmSktQWsgybzjBWlmMskHI1vI9wL3hsheNtxu07bINzj+L+e1VqbJVtK6LOZ0/i8k7FXMzYykdUmZjg2YwxFjjI2MkgkubuWkN32Wl4fcStX2uJXE+vqClRj0rgb/ACC35w3fShbUjlaGxCAc4cHc7iX7tLy0cwaCcrTmgOIPDnOZilpizpu7pPJ5eXLNOVNhlul15OeeJrY2lsjdy8tJc0jm777LJh4Yaip8QtbPY/E3NE6x5ZMgyaWWO/WcKgrubGAwse13Iw7uc3bd3Y9kGLpn2QGRytnSl3L6MnwWltWTtr4bLPvsmlc97HSQdeANHS6rWkt2c/YkA7brUY72SuWk4X5XXtjQvkumse2xGHtyodLPNHZ8nAYzpACIncukc4cvI/0XAAn96f4Na5nZoHAamyeDk0rou1Baq2McJvLci6vG6OsJWOaGRAAhzuVz+YtG226ptAcP9S6C4IM01UdhLmoIpLb2C4ZJKEjZrckvI/ZodsY5OU9ux+MeIS3E7ilxAocPdOZahgMficje1Lj6RjhzTLMNitLNGByTCA+jKXGMnlBaN3Dm7A1Gb4tajp6gx+lsVo2DM6vdjBlcjSblxDUoxF5Y0eUOi3kc5zXBo6Y7NJOwUTQ9jvqWtw9zdCG1g8RlptRVdR4vEUTM7E0HwPieIWktDwyR0bnO5WgAv7N7d6W9ofiLW1dW1viBpdupLmK805bGWrFjyIiOZ8kEsUrY+cuaJHBzXMAO/YjbdBjR+yQs52bRFXTekZcpkdTQZAmtcvNq+QT03sZNHM7kf2DnPHM3f3rdmnm7YGs/ZWVdJ57IYduPwkt7DwxnLRXtT1qLmzujEjoarZWh1gtDgOYiNpJ2333A2GgOA2T0TqLQeQkydXIHEVsw7KzkOjfYt3popi6JmxHIHNeO7gduXx77fS5wx1vpPXGqcrouTTN3GalnZenr6ibMH0bQjbG58ZjaeoxwY0ljizYjs5B1rQWp6WtcJp/UGNL3Y/KQQXYOo3ldySNDm8w9R2PcfGukqIxDDHYpscGBzXMBEY2bvuPAeoK3QEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEWJlctSwdCxeyFqKpUrxumlmldytYxoLnOPzAAleB/ZgcdeN3DnjrhaGgM9kJcDqmlWlwtI4OIsMxAY+CMyRl0r9yyR3Ns5vXDSAANw9i4b91etf6Ui/6Gqt2ubcHqmrdN42SjxGyNa7rPJFmQnsQRtiim+xRxljA0BpMfI1juX8F3g8b9JXr16cmd0fKGUiIi1sRERAREQEREBfmT3jv5iv0sHM5avhqElid3q5Y4293yvPZrGNHdziSAAASSQrTE1TEQNZws0r5Pw+0RNVzGVrRxU4bcsBtddlgyQtLo39YPc2ME7tawtDOwbs0cqoqFHU1F2MimytDKQtlm8ummqOhmfGdzF0+VxaHN7B242cO45fXk6MxUuB0fgsZOOWalQgrPG4OzmRtae48e4W5XDjTFWLVMa5We9O47OZ7mxEOU006GxbdO23Njb0dirR5NzGXPk6UjxIOw5IiQTs4Aekv5jtfYq83EtmFzF2co2Z1erkqcteX7Fv1A4OaOUgDcbnuO43HdUaLSjExWXoZ3Hw3sbdr5GjO3nis1JWyxyN323a5pII3B8PiWWtPPo/BWb1O7JiKRu0o5Yq1oQNbLAyX9dax4G7Q/wBYBG5AJ8FiVdFR4uKnFjcvlqcNStJWjikuOtNPN3D3mfnc9zD70l3h2O47IKNFOQ0tU0BWa3J47KxxUnsk8qqugmntD3jzIxxaxh8HNEZI8QfgozP5uqIhkNNyEtx7rViXGW2WImWG+NePn6cjyfgu6bQfXynsgo0U27iDhK0bn5GxLhhHjW5Wd2UgfWjr1z2JkleBG1zT75pdu3xIA7reU79XIRMlq2YbMb2Nka+F4eHMcN2uBHqI7g+tBkIiIC1uSw3nGdsnW6ezeXbl39Z+f51skQaL2r/yn+z/AM09q/8AKf7P/Nb1EGi9q/8AKf7P/NPav/Kf7P8AzW9RBovav/Kf7P8AzWs0ziJMtgKNyaWtFLNEHuZSlFiEH8CQbcw+fYKwU7w8gNbRGGiNXHUiyu0eT4l/PVj+aJ3rag+vtX/lP9n/AJp7V/5T/Z/5reog0XtX/lP9n/mntX/lP9n/AJreog0tfTnQnjk8o5uRwdtyeOx/nW6REBERAREQEREBERAREQEREBERAREQEREBERAREQEREBEWBnc9jdMYqxk8vfr4zHVwDLatSiONm5AG7j27kgD4yQPEoM9FP287lLM92riMO589WxDE6xk3mtWkY4B0j4nBr3SFjfVyhrnEN5h6Tm/w6WnyEhdmMrZutiyQv1IqrnU2QtaPscT+m4GVo98RIS1zu/KAAAGRLq7GNyFWlDM+9YsWJKu1GF9hsMjG8zxM9gLYdgR3kLe7mgbkgHFqHUeajozziDTkLm2BapbCzZ7+jA5soPTYQN3uHJIN+UA7Al27pUK2Ng6NStFVh5nP6cLAxvM4kuOw9ZJJJ9ZKyEGkw+jsbiJKVgxuyGTqV3VY8rkHde303OD3t6ru4DnAEgbD0W9tmgDMuYDF5DK4/KWsbUs5LHdQUrk0DXzVuo0Nk6byN2cwADuUjcDYrPX5kkbExz3uDGNBLnOOwA+MoMbJ4ijmq3k+QpV71fmD+lZibI3mHgdiCN/nULlNA6Xuy2MbhdJYRl4RCTy+fDxvqRfZeRzeYAB8gDZDyNPYtHOWhzeam8rvagtM8glkxtCrajc+06JknnCLp85bCdzysLnMBeRuQ2QNA3bINri8XUwmPgo0K8dSpA3kjhibs1o//wC7/OttOLiURaiqY/ysTMdyYpcHtEUGStj0riniSV8zjNUZIQXHcgFwOzRv2aOwHYALI9yzRnySwn/p8X5qqUWecY23PGVyp1pb3LNGfJLCf+nxfmqG43nh7wV4W6g1hf0ngXjH1yYIHUIh153ejFH73f0nkb7eA3PqXYlq9RaWwur6LaWdxFDNU2yCVtfI1mWIw8AgODXgjcAkb/OUzjG254yZU63hH/6cvEfD8WG6o0jq7C4zL56q92XqW7NGN73V3vDZI9y3s1j3M5R8Umw2DQF7Z9yzRnySwn/p8X5q1HCnQ2mMFVtZPE6f0nj8gbmQpG5pnHxwN6LLkjWxOc1oPO0RsEo8Oqx+3YBdATOMbbnjJlTrS3uWaM+SWE/9Pi/NQ8K9FuBB0lhNj/8Ax8X5qqUTOMbbnjJlTrc1Zwv0rpQtik0liruEaKtWryY3ym1A47xudM93M6Rm/TJkO7hu9zzyguFbhNHabw8kdzEYTF05C3dlinVjYdnDxDmjwI2/nW9U3Pj5tJRus4mDnxEEM8suFqV29SSV0hl54XbjZxLpN2HcOLm7FnKeeTj4tUWmuZj1lLzrUiL517EdqJssTw9h32I+MHYj5iDuCPUvotCCIiAiIgIiIC0mR0TgcrLbms4mqbVup5BNbjjEdh1ffcRdVuzw0HuAD2Pcd1u0QTk+j5GCd2OzuVxsjqDaMO04sMh5feyhszXgyeoudvzDx3PdLUGq6TLr6drFZTatGKla3FJVcZx+uOlmYXjkcO4DYt2n+EPCjRBOXdTZLFjJSWdN3Z69SGKWOTHSRzusud2exjCWv3YfjA3Hh37L9XOIGAxZyPnLIsxEePihmtT5NjqsMTJSAw9WQNYdyQ07OOx7HY9lQr8vY2RjmPaHNcNi0jcEIP5HKyXfke1+3Y8p327A/wDIg/1r9qfymgNPZduWM2LhgsZVsLb1ykTVtWBCd4eaeItkPJ8H0u25A7Er85HTF+R2Xmxuoshj7V90L2GQR2Iapj2BEcb29g8DZw3+ccp7oKJFO336rpnJy04sRlmmWI0Kkr5aTmR9hKJZQJQ5w7ubsxoPZp298lzVs+MdkHXdP5VlatPFDFYrRNteVNf/AKxkcTnSBrT2dzMBHiNx3QUSneHtV1LROGgdRpYx0ddrTTx0nUrxfgsd6x86+7NbYJ1i3A/KVoJqtplKVll/RImcN2MHPtzFw8Nt9/Vusfh3VFLRGGgFKnjRHXa3yTHzdWCL8Fj/AIQ+dBRoiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIsHMZqngq0c92UxskmZBG1rS90kj3BrWtaASSSf6huTsASgzlqsnqahi7raDpDPlJK0tqLHwDmnljjA5i1v8AOQ0EkDcgb91jQRZvK24prLxhata5NtVrvbO67AByxmRxb9jBO7+Vm57M3cPSas7A4DH6ZxVfG4ys2rTgaWsjaS49yXElxJLiSSSSSSSSSSSg1T2ai1BA4dQ6Yp2sc3YsEcuSqWXHd3j1IPQb28JGlx9bW+ln0NMY/H37F9sTpshYjhimtTvL3yNjHoDv2bsdzs0AbknxK2ynszkbNa85kcpYwAdgB8SChRSHni59vd9ATzxc+3u+gIK9FIeeLn2930BaurxCo3s7awlbP0rGZqsEtjHRWY3WIWHbZz4weZo7juR6wg6BNNHXjdJK9scbfFzzsB/Wp/yKXV7S7I1pK+EkjnrS4e9DG7ytpfyiSUbu9BzGkiM7Etl+yNDhyt0Gdy9cYyS7m7NePGUuW6+S/wAjYYDEeoJnl3ot5C1rw4+9LQexHba47OT3ZKr47QmglLXNewgte07bEEeIIQVqIiAiIgIiIJ/REolwthwdinAZLIN3wx3g7XJhs7+O7fZf43qKgU3w/fz4GyS/Ev8A1VyQ3wrdoO16cbO/jh4TfxolVIgIiICIiDS2cI+jfdfxDK9WWxY8oyMQhG9/aLpglwI2kAbEA877tjDD25S3YYvIMyuNq3GRTQNnjbIIrMZjlj3G/K9p7tcPAg+BBWUtLew8lTIHJ4mOrFcnkjF7rNf/AKRC0EduU7CQAjZxa7cN5OwILQ3SLCw2YqZ/GV8hQl61Ww3mY4scxw9RDmuAc1wIILXAFpBBAIIWagIiICIiAiIgIiICIiAiIgIiIPhbpV8hD0bUEVmLcO6czA9u4O4Ox9YPdQmhOHeHg0Vi44MZDpyV80WQmh05fkihM7Rt7+Nw6rSAAQ7drvWDsuhKd4eVfItEYaA0aeMMddrfJMfL1YIvwWP9Y+dAkwWcrGV1HUj5DLkG2nMylOOdkVf4daLpdIgHxa95e5pPfmGzV/fOOpKb9p8PVvMkyfRY6jb2MVIjtPIJGt9Np7OY0ncdwSfRVCiCdj1xSjMDb1TIYuSxfdjoWW6j9pJB71wczmaGO+C4kA+Hj2W1xeax+chkmxt+tkIY5XwvkqzNla2Rp2cwlpOzgexHiFmrU3tKYbJz1J7WLqTT1LXl0Erohzxz7bdRp8Q7bsT6x2PZBtkU/U0i7GS0/Ic3loK0NmWxLWmsC02wHjvG58we9rGnu0Mc3l22976K/GObquj5oguvxOZaTOMjfhElFzB3MBigPWDyezX80jB4uH8BBRopyjrIubi48phcrhbl6KWQwTV+uyv09y4SzQGSJm4HM3meOYdh6W7R926moZvARZLDZKtfqzsbLDZqStkY9hdtuCNwRuCP5wUG8RSHni59vd9ATzxc+3u+gIK9FHPzlqIAvtcgJDQXbDuTsB/WV+vPFz7e76Agr0Uh54ufb3fQE88XPt7voCCvRSHni59vd9AWrpcQqOTzNzEU8/St5akA61QgsxvngB8C+MHmb/WAg6Gihspq0YPHWMhksnDj6FZhkmtWpGxRRNHi5znbAAfGVssXlrFq5ADOZInn1bbEIKdERAREQEREBEXwu246FSWxKQGRt37ua3c+obuIAJPbuR4oMTL5gY59etFGZ8hc52VYeR5YXNYXbyPa13SZ2AL3DbdzWjdzmtPzw2DdRmkvXJm2sxZggit2Ig9kLnRtI+xROe/pt5nPdy8xPpd3O8V+NNUJ44JMjeimrZPINjls1X3DYZWcGAdKM7Boa3v71o3JJO5O63KAiIgKU1CdshJt48o/5KrUrn/2yf8A+Ef8kHmfT/FbVV7gjwZz8+U58vqHNY2pk7Hk8Q8oile8SN5Q3lbuGju0AjbsQsHD8YtUaMdra5rrNWY8/icfksjBpCbFxQVbEMLi6GWpaaOaVnIGh+7nOBeSQ3l73FL2NGAoSYKKPPaiOJwWUZlsXh3XIzUqSNe54Y1vT5nM3cRs9zi0HZpatjS4B4UaidlszmM7qstr2qlennbjZ4KsVkATsYAxpIc0cvpl2zew2Qc+4fan4v5bM6enuV85ZxOWYfOMt7H4uvWoNfEXMmquhsPlcGv5AGytfzNJJII2UdoexqDh3wH1dqqpqGS3lrOrfJxZno1Q9pOaFed5LYhzmVju/NuG7Dk5Ngu8aF4NVeHNmsaOqtT3cfUhdWo4nI3xNUqsOwa1rQwOcGgAN6jnco8F9m8EtPHhzltFTSXbGIyVqxdkkfMGzxyy2DY5mOa0cvJIQW9jtyjff1hzr2ROq8qLXEPTPlX6iHhrkciavTZ+yOd0fPzbc3vTttvt8267lw+/c1pr/dK3/saoKn7H7C+d8vksxms7qa3lcJLp+47LWo3NkqPdzEBscbAw+I3bt4kkEndXvD/TEei8HhsHDfvZOGiGwx2clKJJ3MDvRDnBoB2GzR28AN9z3QdOREQEREBERBOaCn8owdl3UxUu2UyTObDtLYRtdnGzgf8AXDbaU+uUSFUandCTGfB2XGfGWCMpkW8+Ibywja7MOV38a3bllPrlEhVEgIiICIiAiIg0VmO3idQxWYI71+pknsgsR+UNMNEtY8iZrHels88jHBpOx5HBneRy3qws1hqWosRdxeSrMuY+5C+vYryDdskbhs5p/nBWJpW9YuYrp3nVPOFSV9ayynYM7GOafR3J9IOcwseWu7jn7k+JDcIiICIiAiIgIiICIiAiIgIiICneHlTyDRGGr+QVMX067W+R0ZutBD+Cx/wh86olO8O6fkGiMNX831cV067W+RUZutDD+Cx/wh86CiREQEREBERAU/qTAYyw+PKy4+q/KVmOhhuuhb1o43uBexr9uYNcQCQDsSB8SoFrs9+1kn84/wCaDzvrjKaqyfGvDaOwep5NOY2zp61kp5YqUNibqR2IY2lhla4A/Ze+4cNgewJDhD6b4sa313W0LpaHMRYbNZGXMNymoK9KOR7mY+wYPsMLwYw+QuYTuCG+lsPBd0n0NQn4g09YOmsDJ1cZNimRBzeiYpJY5XOI5d+bmibsebbYnsfESEnsesA3DY6nTymZxl7G5G5kqWYpWI2XK8lqR752NJjLDG7nI5XMPZrd9yN0HF9dZzU+saGI0/k9TSxZjTfEehiTlaVOBhtMe1ksFh0b2Oa2Rgk2LQOUkd2kdh6txdWxj8VVr2b0uSswxNZJcnYxj53AbF7msa1oJPfZoA79gFz1/setMv0JNprynKtfNkm5p+bFrfIuvh4eLXVLduoC1o97y7ADbZXeBxE2Bw9ai/I3Mw+Ecpt5F7XTyd+5cWNaCe/qAQcL0/xW1Ve4I8Gc/PlOfL6hzWNqZOx5PEPKIpXvEjeUN5W7ho7tAI27ELBw/GLVGjHa2ua6zVmPP4nH5LIwaQmxcUFWxDC4uhlqWmjmlZyBofu5zgXkkN5e9vQ9jVp+m/BxxZ7UZxOByrMrjMO+3H5JUlY9zwxrenzOZu4gB7nEA+iRutlS4B4UaidlszmM7qstr2qlennbjZ4KsVkATsYAxpIc0cvpl2zew2Qc70HqTjDmspgZbUWdkxeYicMhYu47FwVse2SFzo56jop5JHcj+TZsrX8zSd9j2UtwwuZ7h97H+jqKnn5LGRzGr2VppZqVYODH5l8E+7hGC8yDckuJLd9mloAA7toDgxV4d3KzqOqNT38bThdXp4jI5AS1KsZ2Aa1oYHODQAG87nco8F/Y+B+nm8Ln6DdNfkxJsSW2WTM1tqKZ1p1oSMe1oALJXbt7eDQDv33DlnsmtWZV7eKOmXWt8JFw+GRZV6bO1h1meNz+bbm7tY0bb7dvDfdel9K+GM/2bP8A2rlcPseMFPd1DbzOYzupLGew/mO+/K2o3c9fmc4FojjYI3emfebDtvtzEk9J0BgBpbH4jEtv3cm2mwQtt5GQSWJAPAvcAATt2329SDoiIiAiIgIiICms+yPOagxmHeMTcqwFuRu1Lby6y3pvDqskcY7bCZnNzu7AxDYE920qm9NSsyWf1JkGzY201thmPilpxbTsZCwF0U7z75zZZJyGjs0O+MuQUiIiAiIgL4S0a87y+SFr3H1kL7ogxfNdT7nj+hPNdT7nj+hZSIJTNw1Wat01RZYlqmU2bDq0VYPjtMZHylsjz7wB0rXDbuS0eoFUPmup9zx/QtNlbzItdafqnJ2K75qlx7ceyHmishpg3e9+3olnMNhv36jviVGgxfNdT7nj+hf1uNqscHNgYHA7ggeCyUQEREBERAREQT2hXl+Esl1jGWj5zyI58Q0CEAXZgGu2/wBa33svxytkVCpzQL2vwVktkxUo865Ic2GZywbi7OCHD7cD2lPrlEh9ao0BERAREQEREBTmLa2hrfOV2+Z4I7tevfEVZ3LfmmAdDLLO3wcwMirMY8d/Rc09mt3o1O2D0+IdDY4ZpmxVncSDbJP5JoNun8cDeoef4nvi+NBRIiICIiAiIgIiICIiAiIgIiICneHdPyDRGGr+b6uK6ddrfIqM3Whh/BY/4Q+dUSneHdPyDRGGr+b6uK6ddrfIqM3Whh/BY/4Q+dBRIiICIiAiIgL8SwsnYWSND2n1FftEGL5rqfc8f0J5rqfc8f0LKRBi+a6n3PH9Cea6n3PH9CykQTmoMY6tYxluhiXZGZtlleaKO0IWsgkcBJK5p9F/IAHAe+7ENPcg7nzXU+54/oWm1zixlsbj4nYh+aEWVo2Oiyz0DEY7Mb+vvuOYRcvULPhcnL61RoMXzXU+54/oTzXU+54/oWUiDF811PueP6F+o8fWieHshY1w8CB4LIRAREQEREBERAU7oCwbumYrhtY+8LdixYbZxkfJBIx8z3MI+NwYWhzvhOBPrW/llbDE+R7g1jAXOcfAAeJWi4fPdLoPTkr7VK8+THV5HWsbF0q0znRtJkiZ8Fjid2j1AhBQIiICIiAiIgIiIJ7KXjDrfA1PONiATVbjzRZX5orHKYfTfJt6BZzdh8Lnd/BVCv8AObjzxg9kho/2Ux4e4DWD21s1da/AsGKpmMVZ3+iCXQkuEWzmFztz9jcd+5J/0OxFWzRxNKtcuvyVuGBkc12SNsbrDw0B0hawBrS4gnZoAG/YbIMtERAREQEREBERBO6De6TB2S+TESHzpkRzYT9Y2F2cAO/jgO038cJVRKd0G7nwdk9TEyfqpkRzYUbQdrs/Z38cPCX+NEqokBERAREQEREBT9xo9v2IPNiAfNl0csw/VE/ZaveE/aPtv4Rr/EqBTt1u/ELDO6WKO2LvDqzO/VBv2Wp6MI+0nbeQ/wAJsHxoKJERAREQEREBERAREQEREBERAU7w7p+QaIw1fzfVxXTrtb5FRm60MP4LH/CHzqiU7w7p+QaIw1fzfVxXTrtb5FRm60MP4LH/AAh86CiREQERS+p81dOThw2MlbUsyQmxNccznMMfNytDGnsXOO/j2Aaex8Fsw8OcSrJhYi6oRQTsRnCSfbnl27+oV6Ow/wD86/nmfO/LTMfV6P8Ahl1Zr5459FtvXyKB8z535aZj6vR/wyeZ878tMx9Xo/4ZM188c+hbevkUD5nzvy0zH1ej/hk8z535aZj6vR/wyZr5459C29fIoHzPnflpmPq9H/DJ5nzvy0zH1ej/AIZM188c+hbe81+zv9kPxC4Gag09BS0/pzNaRvvhuU5shXtGaK7XlbIGudFYYDs5sbwOXYjcHfYr0/wbzeqdS8L9OZfWlSlQ1Lfqizbq4+N8cMPOS6Nga9znBwYWBwLj6XN4eCjdfcG6vFHG0qGqc9ksxTp3I78EU0FMBk0e/K70YBuO53aexB2IKp/M+d+WmY+r0f8ADJmvnjn0Lb18igfM+d+WmY+r0f8ADJ5nzvy0zH1ej/hkzXzxz6Ft6+RQPmfO/LTMfV6P+GTzPnflpmPq9H/DJmvnjn0Lb18igfM+d+WmY+r0f8MnmfO/LTMfV6P+GTNfPHPoW3r5FA+Z878tMx9Xo/4ZftlTUWPPWg1LZyUjO/k2Sr1xFJ+CXRRMc3fw5hvtvvyu22MzXzxz6Jbeu0WBgsvFn8LRyUDXMitQtlDHjZzdxvyn5x4H+ZZ646ommZpnvhGFmpvJsNfm6sMHTryP6tgbxs2aTu4fwR4n5ljaTcXaVwzjNVsE0oT1aLOSB/oD0o2+ph8QPUNl9dRydHT2Uk6teDkqyu6tpvNCzZh9J49bR4kfFuv5puTq6dxb+rXn5qsR6tRvLC/0B6TB6mnxA+LZQbJERAXys2YaVaWxYlZBBEwySSyuDWsaBuXEnsAB33X1XION+oZJ71HTsTi2Dpi7cAHaQcxbEw/NzNc4j42N/r7OydmntWNGFGjX6KxdTcZ8lk5HxadYyhS8G37MfNNL87Y3ABg+Iu3J37tapKXVOpZ3l0mp8mXH+A6Ng+hrAFr0X3+F2Ls+DTk00R/mLzxljlT4M32x6i+U2W/HN/NT2x6i+U2W/HN/NWEi3+wwtiOEGVLDvY+bJ6nxmo7WSuT53GRyw08g9zTNAyQbPa13L2BHb+s/GVufbHqL5TZb8c381YSxMxk4sJiL2Rna98FSB9iRsYBcWsaXEDcgb7D41JwcGNM0Rwgypbj2x6i+U2W/HN/NX9bqXUbDu3U+V3+eRh/4Fuy0WAzMGo8FjctWbIytfrR2omygB4a9ocA4Akb7HvsSs9IwcGYvFEcIMqVdgeLeo8LM3zg9moKW/pNcxkNlo/Bc3ZjtvicBv/CC7Rgs9R1JjIb+PnE9aQePgWn1tcPFrgexB7heaVU8LtRSaf1nWqF5FDLkwSs+C2cNJjk/nIaWH4+Zn8ELxPxH8Nw68OcXBi1UadHdMeixN3fURF8SCIiCd0G4uwdkl2Hd+qmRG+C/Y/7Nn99/H/bv47qqiU7oM74Oz6WHd+qmR74Mf6P+zZ/ffx/27+O6qokBERAREQEREBTl5hPEXCu2w/KMVfBM37Zd5qf6z/Edvsv4Xk6o1O3XAcQ8M3lw5Jxd4h0x/VIfZqnaH+I7/ZfwhXQUSIiAiIgIiICIiAiIgIiICIiAp3h3T8g0Rhq/m+riunXa3yKjN1oYfwWP+EPnVEp3h3T8g0Rhq/m+riunXa3yKjN1oYfwWP8AhD50FEiIgKGyH75tj+h4f76VXKhsh++bY/oeH++lXZ2Xvq9Oix4tsiLTZbWGKwmocFhLdgx5LNvmZRhEbj1DFGZJNyBs3Zo9ZG+/ZbkblERUEREBFG6N4n0td53MUcXiso6hjZ5qrs3NCxlKeeKTpyxRHn53FruYE8gb6LtnHZWSneCIioIiICIiAiIgIiIPhwt/e+wf+w/7lVSleFv732D/ANh/3Kqlydp+PX6z81nvlrtRydLT2Uf1a8PLVlPVtt5oWege7x62j1j4t005J1dPYt/Vrzc1WI9So3lhf6A7sHqafUPi2TUcnS09lH9WvBy1ZT1bbeaFnoHu8eto9Y+LdNNv6unsW/q15uarEerUbywv9Ad4x6mn1D4tlzo2KIiAvP8AxVjfHxLvl5/XKVZ7P/DvIP8AmHL0AubcY9HT5arWzePhfYuUGuZNBE3mfNASCeUeJc0jmAHcjmABJAXsfhWNTg9pjL0RMWXc5EixrTDkcdK2rcdWdPERFbrhj3M3HZ7eYFpI8RuCPmKlm6J1AHAniFnHAHwNPH9//wDMvvaqpp7qZnh9Za1kvKug9MW9bUKmcuapwGH1e/KObYsTQTedIbDZz/o/MbQbsQOQR9PlLSPR9a7zHorPskY53EDOSNBBLHVMeA4fEdq263TtH4F+bGZdhMc7LjbbIGpGbH4zbm/4rkxcKceYmqLRGv56J74+qvO+o9P0BoXitqjonz/idR2ZKF/nd1KpY+FwEff0QS52+3jv33W11dR0/qnUHFV+sJoX5PEV+niKtuyYxWrmqHtlhbuPSdIXbuG53AHzLvMmmsRNSu05MVSfUvSOlt13V2GOw87czpG7bOJ2G5O57BfHMaOwGobUVnK4PG5OzE0sjmuVI5XsafEAuBIC1T2ObaLfy/XkNdws/ex0h/Q9P+4YqhSl3ReSfY2xmrclgsexjI4MdRqUuhAxrQ0NZzwOcB28CTtv22GwXw9pGoP/ANws59Tx/wDhl10zVREU5M6PTqiyX2xcbptSadjjBMhytRwA8dmzNc7/APq1y1ODx1rFUBBcytnMzBxPlVuOJjyD4DaJjG7D+bddM4PaTkymaj1FOwtoUw9tMubt1pXAtdI38FrS5oPrLnfEtfasenAwKsSvRo5+EMqe+7tSIi/M1EREE9oUg4Szt5n2855H9ojvX/Zs3vv4/wC3fx3VVCp3Qf7SWv2m/bTJftD+x/2bP7/+P+3fx3VVEgIiICIiAiIgKeuh3ugYfaPFFvmu9vJMR5waerU2EPr6J79T8IV1QqcvNHui4V3TxRcMVfAkmd+qA+zVO0I9cJ/1h9ThX+NBRoiICIiAiIgIiICIiAiIgIiICneHlPzfojDV/N9XFdOu1vkVKbrQw/gsf8IfOqJTvDun5v0Rhq3m+rielXa3yKlP1oYfwWP+EPnQUSIiAobIfvm2P6Hh/vpVcqGyH75tj+h4f76VdnZe+r06LHi2y89eyH0hpLPcaeD02rMXjLeOsTZKnYkycbDE/ao58Ubi7t78EtB9fh3XoVazUWl8Nq/H+QZ3EUM1R5xJ5LkazLEXMPB3K8EbjfxW2YvCOG6b0HpzWfsmeJWQytCHLx4yngZ6Ecn2SGN/Tnc2VrPel45G8rttwC7b3x35HonI0jxI4V68wken9MDVmdsQPxdG1PNk56z4p+byx75S1/ptjPJ0/sbiwB3bZe0cdp7FYe1PZoYynRsTxxQzTVq7I3yMiBbE1xABIYCQ0HsATtstXDw00hWuz3IdKYSK5PZZclsMx0IkknY7mZK5wbuXtd3Dj3B7grGaR5PGlMXi+EOW15WrmPVuN4hStq5TqPMsMbs6InxNO/oxuZI/mjHokuJIJJKrcfh9P6L9kPI/LRYjWcmrs1drVMvWvl+Rxkjq7+pRsQcxDoGsa9oI95uOZoOxXo92jsA/Fy4x2DxpxstjyuSmakfRfP1Or1SzbYv6gD+bbfmG++/dfKnoTTWP1FPn6uncVWzs+4lykNKJlqTfx5pQ3mO/zlMkeR8LpzG6H9jJqG3hKrNPVcjrGTH53I4/eGVmLZmJIX+m3uGshc5u/wAFrneC+fFzG6d0h7qun+H5rw6Vk4ey3cnSx0/VqQ3euGwP8SGyPiMu4GxcGNJ38V7IqacxNDGz46ti6dfH2HSvmqRV2NikdIS6QuYBsS4ucXEjuSSd91rsfw30licFdwtHS+FpYa9uLWOr4+GOvY3Gx6kYbyu3+cFTIHCeIvCbS2Ds8HsRVxbGVcrqRpyb+d3VyDhjbQLp3780hd3DuYnmBIO4JC5tqrh3p7TXDjjzmMXjxSyOkc9zafnileDig2GrMG1xvtE0vkeSG7A82x7Abe1LmEx2Qloy2qFWzJQl61R80LXmvJylvPGSPQdyuc3cbHYketYlnR2AuU8rUsYPGz1Ms/q5CCSpG6O4/la3mmaRtIdmtG7t+zQPUFZpG4XmjUGM0prT2Q+vKPEizXfFh8XQm07RyVw14Y4HxvNizEOZoMnVbymQd2hrRuF1vIcPtTXL9meDifqKjBLK58dWGji3MhaSSGNL6jnEAdgXEnt3JPdbK9w1weocfjotT4+jq2/RZtFkszj68s4d/DG0Yaw+HvA0dlZi481exhy1bGak4dWsnciqsscMm8s9qUMEjmXi6T0nHuQHAn5juofT0smsNPcLcBYyuFqaOytjUlqJ+ehlnxt623JymJkjY54eYiNz3MDnFpJPok7EestD8ENP6c4a6U0lnaON1aNPV2w17eRx0bvTH+sYx/PyHw8CfDxVNa4f6Xu6f8w2NN4ixg+o6bzZLQidW53OL3O6Rby7lznOJ23JcT4lYxTNh5dy3DKGlp/hpgbep6Op8Df4ic8LMIZIqtSHyKy2SnGTPK4R87JAW8/bnc3sOy33Fx0fsZNSHI6OxMdDH6twz8BToUIgyKPMxuc6i7lHYc4mmaf9m1ei6+jdP1KeNqQYLGw1cZL5RRgjqRtZUk2c3niaBsx2z3Ddux2cfjKntW8NJda6407lslmC/AYKZl+tgmVWAPvtEjWWHzElxDWydmAD0m7knwFydQ2/DrRsHD3Qen9NVndSLFUYqnU9cjmtAc8/O527j85VEiLMfDhb+99g/wDYf9yqpSvC3977B/7D/uVVLl7T8ev1n5rPfLXajk6Wnso/q14OWrKerbbzQs9A93j1tHrHxbppt/V09i39WvNzVYj1ajeWF/oDvGPU0+ofFsmo5Olp7KP6teDlqynq2280LPQPd49bR6x8W6abf1dPYt/Vrzc1WI9Wo3lhf6A7xj1NPqHxbLnRsUREBERBzzVnBuhnLUt3FWjhLsri6QMiEleRxO5c6LduzidyS1zdySTue6jpeC+rGPIit4aZu/Zz3yxn6OV3/Nd0Retg/inasGnIiq8b4v8A9W7g/uM6w+3YP6xN+iT3GdYfbsH9Ym/RLvCLf/We1buBo1OD+4zrD7dg/rE36JPcZ1h9uwf1ib9Eu8In9Z7Vu4GjU4P7jOsPt2D+sTfol+mcGNXOOzrGFYPjE0zv+HTH/Nd2RP6z2vdwNGpyvAcDIo5mzZ/JnJMB3FKrGYIT8zzzFzx827QfWCuowwx14mRRMbFExoaxjBs1oHYAD1BftF5naO1Y3apysWq/81FxERcqCIiCd0J+09wb4btlMh2wX6wP9MmPp/x/f7N/G9RUSndDnahkmb4b0cpd7YTtGN53u+yj7f33l/DLj61RICIiAiIgIiICnbjObiFh38mJPLi7o55T+qLd5qvaEfaTy/ZPwmwKiU5OOfiHSP6jHp4qcen+2beaaH3nxQHk9P43tj+JBRoiICIiAiIgIiICIiAiIgIiICneHtI47ReIrOxtbEGKHk8hpzdaKHYn0Wv9YVEpzh5SGO0djqwxtfECIPaKVWx144h1HeD/AF7+PzEkepBRoiICh8iNuJk5PgcRCB8+00u//MfSrhc3445b2q6StahxsjfbRThezF0hG6Z2TmLS5tLpN9J5lMZDS3u0jm7gOB6cCumiqcrumLLClReQ/Y4ey34j+yT1e/FYTRWLo42o0SZHMTySmCow+9HY+k92x5WDudiewBI9UeYNYffPB/UJv0y7Pd7cc+i23toi1fmDWH3zwf1Cb9MnmDWH3zwf1Cb9Mnu9uOfQtvbRFq/MGsPvng/qE36ZPMGsPvng/qE36ZPd7cc+hbe2iLV+YNYffPB/UJv0yeYNYffPB/UJv0ye72459C29tEUXra/q7RmOoW32sLaFvJ0saGtpzN5TYsRwB/66d+Xqb7evbbsqDzBrD754P6hN+mT3e3HPoW3toi1fmDWH3zwf1Cb9MnmDWH3zwf1Cb9Mnu9uOfQtvbRFq/MGsPvng/qE36ZPMGsPvng/qE36ZPd7cc+hbe2iLV+YNYffPB/UJv0yeYNYffPB/UJv0ye72459C29tEWr8waw++eD+oTfpl+2aW1Jc+w3s1RgrO7SHH05GTEesNe6Uhh8Rvyk9+2x7p7uP1xz6Jbey+Fw24fYP564II9YJOxVSvhSpwY6nBVrRiGvAxsUcbfBrQNgB/UF915+LX7TEqrjxmZJ0y12o5Olp7KP6teDlqynq2280LPQPd49bR6x8W6abf1dPYt/Vrzc1WI9Wo3lhf6A7xj1NPqHxbJqOTpaeyj+rXg5asp6ttvNCz0D3ePW0esfFumm39XT2Lf1a83NViPVqN5YX+gO8Y9TT6h8Wy1I2KIiAiIgIiICIiAiIgIiICIiAiIgIiIJ3Rx5XZ6LfDbx5Sb0cP2LeYNf8A6QPVOebd3x8zT61RKd0weTOarhJw42yLJGx4wbWA11WDvbH24uD9j64ul6wVRICIiAiIgIiICnYW9XiFbPTxLuhi4R1GnfIs6ksvZ4+DCel6Pxua/wDgqiU7hG9fWGpbPJiHdMVaXWpnmuDkjMvTsn1cvX5mN9TZS74aCiREQEREBERAREQEREBERAREQFPaCpOx2mo6zsXBhunZtBtStN1mBvlEnK/m+N42eR8EuI9SzrupMbj8pQxs1pov3jIK1doLnSdNnO/wHYAEbk7DdzR4uAMdoFudsYqSOrgqmkKE1rI2JYJ7As245pp3yseWMc6NrnOldK9pedi7lA27gL+3bgoVZrNmaOvWhYZJZpXBrGNA3LnE9gAO5JWgn1kLtez7X6UmesNqRW68jCYqdlsn63yWiCx249I8nMQ3Y7ek0H609G1GTQWshPZzWRZQ83S2b0m7Z4yeZ5dA3lhDnHbmLYwSAB4AAb9BN39P5XPx5GvkMu+jQsCDoRYfmgsQ8veUOscxLg93bdrYyGjx3O629DCY/FWb1mnSr1bF+UT25oow19iQNDQ97h3cQ1rWgnwDQPABZqIJ7RHD3TfDbFT4zS+Fp4LHz2pbklalGGMMsjuZ7tvV6gAOzWhrQA0AChREBERAREQEREHPuNbOpp7T7dnE+2fCn0W8x7ZCA/R28fV4roK55xnHWp6QrjbebVGMIBO3vJuqf+EZXQ0BERAREQEREBERAREQa7UcnS09lH9WvBy1ZT1bbeaFnoHu8eto9Y+LdNNv6unsW/q15uarEerUbywv9Ad4x6mn1D4tk1HJ0tPZR/VrwctWU9W23mhZ6B7vHraPWPi3TTb+rp7Fv6tebmqxHq1G8sL/AEB3jHqafUPi2QbFERAREQEREBERAREQEREBERAREQEREE5i3CDXOfgLsQzq1qlkR1hy33b9VhfY+Nn2NrY3fgvHqCo1OWHipxApbyYmJt3HTM5Xt2yEzopGFoYfhRNEjy4epzmkeJVGg+Fy2ylAZXhxaCBs3xWv9stb7XL9A/Kvrn/2tf8A+If81xnV/GCnpPV8WmIsDnM/m5cf5zZWxFeOTeESFjiXPkY1pBA98RvzADcnZB2H2y1vtcv0D8qe2Wt9rl+gflXDZ/ZCack0/pjJYqlls/a1IyR+OxGNqh1x7Yu0xe17mtYIz6Li5wG/Ybqb1v7I59bSulszpbB5HJuyGpIsHkKMtdjLVR4k5Zq7mPlYGznbZu5LfWSAQUHpb2y1vtcv0D8qe2Wt9rl+gflUOzPxQ6a89ZCvYxEDKpt2ILgaZazQzmc14Y5w5mgHflLh27ErnlT2RWJn0FkNYz6a1Lj8HWhq2YZrlOJnlsVh4ZG+H7KQR6QJDi0gEHbuNw737Za32uX6B+VaXTOTbRGVntUqdezdvy2HPxzNuswbRxPlJ7ul6UcYcfAcoA3DQVzzW3F7D6Fyt/HXq92WxT0/c1G90DGFhr13Ma9gJeD1CXjYbbHvu4LXaS454rUWcwmIsYLO6cmzdd1jEy5erHHDea1ge5sZZI/lcGHm5Xhp2B2BQdu9stb7XL9A/Kntlrfa5foH5V590r7JnA6nr6cuv0/qPDYbUE7auPy+SqRNqyTuJayIlkr3NLnAgEtDSfArJd7I7Tbcq6PzdmnYJmSGIfqcVG+bG2up0+Qyc/Pt1DydTk5ObtzIO8+2Wt9rl+gflT2y1vtcv0D8q4nV4308rq7O6dxWmdQ5e7hLXkl6arXhEETjE2Rp53ytBDg7lAHpbjuACCZvhR7ISXUPCafV+r8Jewcdd7wbIgjMNxxsyRRxVmMlkkc/cMYQ4Ddzu24O6D0h7Za32uX6B+VPbLW+1y/QPyrieI474OzPk6+cx2X0Zax+PflpIdQ1mwl9RhAfMx0b3tcGktBG/MOYdu6k8Zx1yOseLvD/ABeOxGe0/gMrUyNmUZrHxwtyDGRxOhfGd3PaBu47HkOz27jYhB6loZCPIRufG1zQ07HmWUtNpn9jTf8Aj/7LcoCIiAi+Nq5DSY188rY2ucGN5j3c4+DQPWT8QU67EWda0nHNxyVMLepNZJgJQGzNeXlzutNHIQ70QxhjYeX9cDnSBw5QybWrGPtWKeJqS5m7VtQ1rccLmxsrdQBxc97yAeVhDi1nM70m+j6QX8jwWUvztlyuXcG18g+zXgxbXVmOhA2iinJc50hHvnbFjXE7Fuw779rQxoDQGgeAC/qDAwuCx2nKDaWKo18dUD3ydGrEI2873Fz3EDxc5xLifEkknclavTFJuOzmqImYyGhFNeZbE0VnqOtl8EQdK9njGeZhZt4EMDvWVRqdMHkGvhYZQpxsyWP6U1/rBth8kDyYouQ++byzTu3Hhsd/EIKJERAREQEREBERAREQEREHPeJP+m634Y44Na/fNzXpAT3EcNC0NwN/tkkI9fj/ADEdCXPGgag47mRrg+DTWDdC7bftYuzMdsfVzNjqNPzCb510NAREQEREBERAREQEREGu1G/paeyj+rXh5asp6lxvNCz0D3kHraPWPi3TTj+pp7Fv6tabmqxHqU28sL/QHeMepp9Q+LZNRv6enso7qVouWrKepdG8DfQPeQetg9fzbppt/U07i3dStLzVYj1KQ2gd6A7xj1MPq+bZBsUREBERAREQEREBERAREQEREBERAREQTuq5fIcjpy8ZsZWiZkBXmlyDPsjmTRvjbHA/4MjpjAO/ZzQ5viQRRLRa4imfpTIyV30orNeMWoZcjCZYI3xOEjXvaO/YsB3HcEAjuAttSuwZGnBbqyssVp42yxSxndr2OG7XA+sEEFBiZ/8Aa1//AIh/zXEnaTyp9kLHqbyX9RBpZ2ONrqM/ZBttk5OXfm96Cd9tvn3XdclUdequia4NJIO5Wn9rM325n0FB5N0Rwx1vw1r6I1JW0355yeMizONyGEZegjm6Fq+6xDNFI53TJAa3dpcDs/4wQsmbhJrVmhbGZOLrzapsa5i1m/T8dxgDY2OjaKomOzDJ04wS7s3m377L1T7WZvtzPoKe1mb7cz6CgjqN/IZTS3lVzBupZGWB5diLM8byHd9o3PYXM79u4JHdebG8GdbZvSWvMNjNOu0Rp6/jq7sdpm9l47kLcjHY6z3QFhcIIXBrW8vYbnflavYntZm+3M+grDzOLlw+Kt3unNdMEbpBWpxGSaUgdmsb63HwG5A+Mgd0HlHinQ1hqa7rPVWX0lJprDVeG+ZxxFm/XsS+UP5JAC2J7gARG4ggn3p35SQDu9F4bWPEfJ8K7WU0uNM6d0rXbf8ALJr8NiTISuqGGNsTIySxm0hcS/YnYDZelbOi25bGT1L8cFqraidFPVtRh7HscNnRvb3a4EEgjuCPjX2raQ8jrxV65hggiYGRxRs5WsaBsAAOwAHqQeK+D+G1jxN4I8MNLs0uMZpqpbq5K1qKe/C9ssNewZgyKFp6ge5zWt3cAG9+5VFLwr157m8vCCPT0IwT8s6Qat8vi6Qom95Xv0N+r19jybcvLv35l6rxOga2Ax0GPxkFPHUK7eWGrUhEUUY8dmtaAAO/qCy/azN9uZ9BQci4V6Tymm9UcSbmRqeTwZjUHltJ/UY7rQ+SV4+bZpJb6THjZ2x7eGxC5E7g5rPMcE7nDi5pytHNhMi7JY7IW7kUtDLht51hsL4wTIwPY4tPO0AH4wvXXtZm+3M+gp7WZvtzPoKDytLwPi1xoDWmIq8KMRwtyuQxZp1L0ctWWSaQnnLHGuDtFzRx9ydyCfRG3fe4urr/AFnxX4eZ3P6GOmamCqZGG7N50rWGOlmjia3ptY4u5CYzsSN+/cDxPoz2szfbmfQU9rM325n0FBk6Z/Y03/j/AOy3KwcTj3Y+J7HPDy52/ZZyAvxLI2GJ8jt+VgLjsCTsPmC/a0Go60+Wv4vF+S3Dj3yeV2bta0IGxGF8b44nbek8SO8Wj0S1jw47HlcH5wkDtQPhzd1j3QvMdnGUrtEQzUAYi0ucHbvErhJICTy8rHBnK0h5fQoiAiIgLRauxli5Tq26FXH2MtjrLLVR+Ra4sj8WTFrmbua90D5mBwB2L+4cNwd6iDGxuSqZnHVchQsw3aNuJk9ezXeHxzRuAc17XDsWkEEEdiCslT9EzYDNGhI6azRvyOfSEFANipBrGl0T3s7AOIe5rnNHclpcSWg0CAiIgIiICIiAiIgLXahz9LS2Cv5fJTdCjShdPM/bchrRvsB6yfAAdySAPFbFc9bvxR1PFKOV+jMLYEkZ7Obk8hE8Frx/E13t3B+FMARsIQZAz+Fen72KwFnJZiLo6gz1p+VyMRO5he8NbHBuPHpQshi3HY9Mn1qzREBERAREQEREBERAREQa7Ub+np7KO560XLVlPPdG8DfQPeQetnx/Nuv5pt/U07i3c9aXmqxHnpDaB3oDvGPUz4vm2TUj+np3KPMlaINqynqXG80LfQPeQeto9Y+LdNNv6mncW/qVpearEepTbywO9Ad4x6mn1D4tkGyREQEREBERAREQEREBERAREQEREBERB/HNDgQQCD2IPrU9oS6Z8G6nJeqX7eNnko2H0oeixjmO9FnJ8EiMx7gdu+47EKiU1UyEeP17dxc2SidLkagyFTHCoWPa2ItinkMo7SDeSuNj6Td/WCNgpUREBERB/HODWlziAANyT6lN41kOr71XNPbWs4quW2MNZq23yNsNfFsZ3NGzCCHEM9/6PpAjm2GRcFjPZKSi0WqWPqPY6xK6KIxXw5ruaAc27uUeiXnlG+4a1x2eBvANgg/qIiAiIgIiICIiAiIgKcwGPEmp9RZifFCjbkfDj4rflfWNurCwvY7kHaLaWew3l8TyhxPcBtGp3QGPOP0tW58VFhbFqWe9YpQ2PKGsmnmfNIep8IufI5xI7bu7dtkFEiIgIiICIiDEyuLrZvG2aFtjn1rDDG8MkdG4A+tr2kOa4eIc0gggEEEArX0Mu+lkfNeUkqQWJpHjG8k7nPtwtaCSQ4AiRu5DgC7cND9xzFrd2sPL47ztjp6osz03yNIZarFolhd6ns5gRzA9/SBB8CCCQQzEXPOIfGvT/BvSGTzutrHmevSlMFdr5YpJsmSAYzXY1wJc7cghwZylkhO0beob2pbhv1IbNeQS15mNkjkb4OaRuCP5wUH2REQEREBFpdaasoaD0jmdR5Rz247FVJbk/TALyxjS4hoJALjtsASO5HdRtTijR4tY3HQcOszBkKuRhZas56sOZmPquJ3ABH7KdyuY2N4BjIc+Rp5BHIGwz1+xr7L2dMYmaSDD1z0s5lK8jmP7jfyOB7SC2RwI55Ad42nZu0jw6O2qVIMfUhq1YY61aBjYooYWBjI2AbNa1o7AAAAALFwOBoaYxFXF4yuKtGs3ljjDi49ySXOc4lznOJLnOcS5xJJJJJWwQEREBERAREQEREBERAREQa7UbizT2UcJKsRFWUiS8N4G+ge8n4A9fzbppxxfp7FuMlWUmrETJRG0DvQHeP8AAPq+bZNRnbT2UO9Nu1WXvkP2MPQP67+B/C+bdNOHfT2LO9N29WLvj/2MfQH61+B/B+bZBsUREBERAREQEREBERAREQEREBERAREQFPawyD8K3FZN+WdjMdWvRsuxip5QLTJQYGRkj0owJZYnmQdgGHm9EkihWJlqLsnirlNlqak+xC+JtmsQJYS5pAewnwcN9x84QZaLVaWyhzOBqWnMtMkIMcgu1+hLzscWPLmeA3c0nt2IIIJBC2qAtDdyUmWyUuKxdiDmqyRjJukZLvHG9hIjjezlAlI5T77djXscWkOZv9srlnvuDF450M+RIjfZYLLGSU68heBOWkOJ3MbwwFuznNIJADiM7GUG4vH16jJZ52wsDBLZldLK/b1ue4kkn4ygYvF08Jjq2Px9WKlRrRthgrwMDI42AbBrWjsAAspEQEREBERAREQEREBERBh5eSWHE3ZIYRZmbA9zIXSdMSODTs0u+Due2/qWJo/FxYTSWEx0FGPFw06MFdlGGQyMrtZG1oja8++DQNgfXtuvlrms+5onUFePGx5iSXH2I246WfoMtExuAidJ8AO96Xerff1La0oG1qVeFkYhZHG1gjadw0AbbA/Mg+6IiAiIgIiINbnNQVNPVmS2TI98juSKCCMySyu232a0dz27k+AAJJAG60J4iSb9tLZ0j4+nX/TL4ZZ5k4kNa7uIcTuz8HnmPN9PTZ9AW0Xo04WHTTGVF5nSy0Q8Teyz9izq3j3qOTUOKzeprEzXE1sJqBsPkVMODQ4QGKTaMEMZv9jJdyguc4916V4Jah1Ho/hLpXA6o0zk5c5i6EdKxJRMMkLumORha50jSd2NbvuB33XREWWThbHOepeNTC90ST5LZ7/yV/0ye6JJ8ls9/wCSv+mWaiZOFsc56l41ML3RJPktnv8AyV/0ye6JJ8ls9/5K/wCmWaiZOFsc56l41OLeypj1Zxe4LZjR+ktOX62QyskMU02RdFFGyBrw9/dj3Hc8rRtt4ErmHsQPY55z2NuSs5jIZHU12zeh6dvC42Cs3Hykb8rnmSUue5u5LXNEbh3G5a5zT64RMnC2Oc9S8amEOIj9/S0xnWN9bjFAdv6hKT9AVHiMxUzlJtqnIZIyS1wc0texw7Frmnu1wPiD3WpWv0g8t1nqiEdozFTmI+N5bI0n6I2D+pYV4VFVFVVMWmOsR9TRKzREXnsRERAREQEREBERAREQa3Uh5dO5Qk1GgVZTvfG9cegf10fwP4Xzbpps82ncWQajgasXegNq59AfrQ/gfwfm2X91G4M09lHGStEBVlJkuN5oG+ge8g9bR6x8W6accH6exbmyVpgasRElNvLA70B3jHqYfUPi2QbFERAREQEREBERAREQEREBERAREQEREBERBPYZsmO1TnKThlrENnpZGOzbcJKsRc3pOrwHxbymESFrt+85LTtu1mxzGTkxzKzIalm3PanbXZ5PFzti3BJkkJc0NY0Ak7uBO3K3dzmtOr1ZBJVu4bL1qNvIW6tkVulVnMYEU7mxvfI3wexh5Hn1gMJHhsc3B4d9VzshkGVJM7YibHatVY3NaWtLiyNvM5xDW8x7bgElztgXEIPvhsUcXUDZZvLLsmzrN10LI32HgAczgwAeAAHxAAd9lsERAREQEREBERAREQEREBERBO8Rsectw91PRGIZnzaxdqDzTJZ8mbd5onN6Bl7dMP35ef4O+/qVCBsNh4Kf4h40ZnQOpKDsS3PNtY2xAcU+x0BcDo3DomTccgfvy8242333CoUBERAREQEREEPk/wB8uT+iI/7562q1WT/fLk/oiP8Avnrar1Z/LT6QsiLlnFfX+rMBxA0FpXStfEvl1IL/AF7WWZI9tYQRxvDwGPaXe+cC31nl9JvcrnWp/ZHauqajzeFw9fG2bOmxHUvy+17LXGZG70WSSshdWa9tZgLw0dR0jt+5G2xOqaohHphF5yxOrNeav9kLpezRt18Dir+jIcpYwOXp2HyV2vsxdaMtEzALAJLRIW7ADYtKp9Ga64i8QNT64r0DprF4fT+btYiCa1UsTzWC2Bj4yQ2ZobyvkYXHvzAkAMLeY3KHZkXknRvH27pbhbw8weCxWOx2azMORvTGHG5HIVKcMVt7HObXhMk7i97+27w1vpbuHotNrpn2QGqrXtYtZzBQ4/Ez6ifpzJW34+3V6rpImup2q7LAY9kbpCInNe1xDiNndu8iqJHoFF5tznsnc3Wp1HUaNIO1Fm79TT9g4+5caMfTDWy2pYq/PLKXyb8jWBg5XNJcACT0bgfxKznEGlm489inVLOMtNhivx463Rr343MDhJHFaY2RpaeZrgeYbt3DiCrFUTNh0xa3SP7utT/7rR/+dbJa3SP7utT/AO60f/nWyfhYnp/tCx4rVEReUgiIgIiICIiAiIgIiIMLNMdLhr7GGAPdXkANlvNFvyn349bfjHxLG0jZbd0phbDJ6dlktKGRs2PG1aQGNp5oh/APi35tltSA4EEbg+IKnuH1nr6RoQutULk1LnoTyYyLpV2ywPdE9jWfA5XMLeX1EEDsgokREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQTnEfHDMcPdTUDh26hFrGWYfND7Xkou80Th0DN26Yfvy8/wd9/UqNTvEXHHL6A1JRbhmaiNnHWIfND7PkzbvNG4dEy/6sP35eb1b7qiQEREBERAREQQ+T/fLk/oiP8AvnrarVZP98uT+iI/7562q9Wfy0+kLKQ1Jw+9sHEXRuqvL/J/a6y8zyTo83lHlEbGb8/MOXl5N/A77+pSmX4L5+lrPP57ROuX6Sj1C6OXKUpcXHeY6djBGJ4S57ek8sa0HcPaSASF1pFrtCOcav4WZbLa/wANrHAaoGBzFPHvxVvyjHttxXKzpGSbcvOzkeHs3DgT4kbLccPOH3tCs6tl8v8ALvP+dnzW3R6fQ6kcTOl74823S35u2/N4du9eito7xwzHexptac0/o0YDV78VqvTAuQwZnzc2WGzXszOkkhmrmT0m7luxDwQW7jx2Vln+F13WvCTKaO1PqJ+XyF+KQHNRVGVnQy8/PDJHEw7DpODC30t/QG7t+66CimTEDlmqOBFW5g9EwaYy8ulMxoxvTw2RZXbYayMxCKSKWJxAkY9gG/dp3AIIVporD53C4h0OotQDUmSfM6Q22UWU2NaQNo2RtLtmjY9y5x7nut+itogFrdI/u61P/utH/wCdbJa3SP7utT/7rR/+dZz8LE9P9oWPFaoiLykEREBERAREQEREBERAU5RtNw+rLeMs3oT5zDruPqMqGMsaxsbZwZAOV5L3Nf39P03eIb2o1gZnGPytIQxXbOPlbIyVk9RwDgWuDuU8wILXbcpBB7E7bHYgM9FrsPl/OUZjnrux+QjHNNRllY+SNpe9rH+g4jkfyOLT6wO4BDmjYoCIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgneIuNGZ0HqCgcQzPi1RmhOLkteTNthzCDEZfgB2+3N6t1RKc4iY4ZfRWXonDDULbEPSdjHWvJRYBIBb1fg9tzv8yo0BERAREQEREEdqqpNi9QQZ5sE1qn5IallteMySRbP5mPDGguc3u4HlBI3adiNyNYdfYQHY2ZgfiNOb8xdERdtHaKYpiK6b21Tb6St48XO/b/AIP7pm+qTfmJ7f8AB/dM31Sb8xdERZ5xhbE8Y+1dDnft/wAH90zfVJvzF8rXEjTtKtLYsX3168LDJJLLWlaxjQNy4kt2AA77ldJUB7IMtHATiTzkhntayQO22/7Fk8N0zjC2J4x9pofEa/wZG4tTbf7pN+Yv77f8H90zfVJvzF0GFhjiY0+IaAv2mcYWxPGPtNDnft/wf3TN9Um/MT2/4P7pm+qTfmLoiJnGFsTxj7TQ52Ne4Vx2bPYe71NZSncT/MAzcrdaMxtjy/LZmxC+qL5ijgglbyyCKNp2c8fBLnPeeU9wOXfYktFUi1149M0zTRTa/fpvv1Ql48BERcaCIiAiIgIiICIiAiIgIiINVmsGciySenOMblxF0ociyFkj4287XlhDh6TCWDmb2JG+xadiMdup20rba2ZhZiJbF51Og58wey56HOwtcAOVxHMOR2x5mOA5hs529X8c1rxs4Bw3B2I9Y7hB/UU5X0zZwDKcWBueT46syxzY22XTMlc88zNpXEvjDH77AczQwloaAG8v59useKrB2pKxwDoceb9y3I8vx9YNdyyNNohrRy7h3phpLTzbei7lClRfiGaOxCyWJ7ZYpGhzHsO7XA9wQR4hftAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERBO6+xxy2mZagwrc+2WxVa+i+z5OCzyiPmkL/AOLbvJy+LuTlHiqJTmtsa7L18PVOIZmIfOtWeVr7PRFYRSCZs/iC8sfGwhnrO2/bdUaAiIgIiICIiAiIgIiIC57x3/0zh3YwjQHzZ+3VwzI9xu5tidkcp7+IbEZXkfwWFdCXPMU9vEnW9PPwu6ml8CJG4yVp9C/de0xyWG/HHFGXxseDs8zTHbZrHODoaIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiIJ7IaHx9p2SnpPnwmSvwRwSZDGOEcwEZ+xkAgsJb4Auae3Y7jsvzebqjGMyM1I47Ot5IBTpWS6lICDtOZJ2iRriR6TQImjmHKTs7mbRognbutquHdkXZWlfxlSnPFCLktfqQz9T3r2GMvIaD6JLw3lPjsCCdzUyVO/LZjrWoLElaTpTsikDjE/bflcAfROxHY/GslafKaQw2Z5zbx0L5HzxWXSsHTkdLH+tvL27O3b4Dv4EjwKDcIp2TTF6u6R+O1BerGbINuystBtlnT+HXYHjdjHeI2O7T4duyeU6opOPUpY7KNkyYjaa8z65gou/1jg4OD5WetoLQ4dxsfRQUSKeZrSKJzG38VlsY6XIuxsPVpumErvgy80PUayJ48HyFoB2DuVxAWdiNT4fUEb34zKU8g1k8lV5rTtk5ZoztJGdj2e31tPcetBs0REBERAREQEREBERAREQEREBERAREQEREBERAREQTmcx3nPV+mXSYuK3Bj3WbzLz7PI6nP0ugzljB9MvjnnG57NAPrIVGprFU/K9b5rJy0KrDBBDj696OfqSyMG8kjXNB2YA57e22523PblVKgIiICIiAiIgIv45waCSQAO5J9Sg7HGPE37UlLStW3ra+wua4YRrX1YnDfdsltxbAwgjYt5y8d9mnwQXqm9VcQsJo+WGrdsvnylgf6PiqMLrNyfx7thjBdy7ju8gMb4ucBuVofa1rbV4cdQZ6HTOOkaP1L0yS6x6tw+7IAdvV9ijicO/pn1Umk9C4DQ9eeLCYyGi6y4SWbA3fPZeO3PNM4l8rtu3M9xPzoJoYDUXEgE6phOndNvH7nIJ2vtWm/wbk0ZLQ0+Bhhc5ru4dI9rixdBjjbFG1jGhjGgNa1o2AHqAC/SICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICwMjgcZmJakt/HVLstOcWaz7EDZHQTAbCRhIPK4DtzDus9EE7W0PRxxqDH2sjj4q9t9www3JHRyuf75j2vLhyE9w0bAHw2SnidRUHUGDPwZKBliR9t1+iOvLC73jGOicxjHNPwix3MPUD3VEiCdo5TUkbsZFksFWc+xLMy1Pjbwkiqsb3ieeo2NzucdiGg8p/hD0kx+tqts4qO1j8ri7WSkmihr26MhLHR783UewOjj3A3aXOAd8HfuqJEGowmrsHqWpTtYnMUclXudTyeSrYZIJum7lk5dj3LHdnAe9PY7FbdYlrEUb1yrbs0q9i1U5/J55YmufDzt5X8jiN28w7HbxHZajG6Bw2E8ysxkdnGVsQJhVp07s0VbaXfnEkIfySAE7t52nkPveXc7hRIpujpvMYuLGww6otXY6sUzJnZStFLJac7cxue6Nse3Ie2zQOYDv39Jfqi/VdY4mK7Fh8iDHL5yt15Japa8frRhhIk5g7sHB0o5fEF3ggokU3U1VkGwVDktM5KlLJWlsT9B0VmOBzD+tEsfzOc4d28rSD4Eg9l+oOIGCk8nE1x2OkmouyQiyUElR7K7ffveJWtLOX4QdsR6wEFEixqGSqZWrDZpWoblaaNs0U0EgeyRjveuaQdiD6iOxWSgIi5ljqEGu6LMxlxJa8pc90FfrPbDDFzkMaGAgc3KAXOI3JJ8BsB0YWF7SJqqm0R9f/ixDpqLnXufae+9rPxj/AMqe59p772s/GP8AyrozfC254R9y6HRUXOvc+0997WfjH/lT3PtPfe1n4x/5UzfC254R9xodFRc69z7T33tZ+Mf+VPc+0997WfjH/lTN8LbnhH3Gh0VFzr3PtPfe1n4x/wCVPc+0997WfjH/AJUzfC254R9xodFWPfv1sVRs3btiKpTrRummsTvDI4mNBLnOcdg0AAkk9gAoL3PtPfe1n4x/5V+J+G+mrUL4ZsTFLE8Fro3uc5rh8RBPdM3wtueEfcaFbo/GOxuDjdNUpVL1t7rlxuPJdC6eQ8z3Bzu7u598dt9vADYDdrnXufae+9rPxj/yp7n2nvvaz8Y/8qZvhbc8I+40Oioude59p772s/GP/Knufae+9rPxj/ypm+Ftzwj7jQ6Ki517n2nvvaz8Y/8AKnufae+9rPxj/wAqZvhbc8I+40Jf2VPsncP7GzQr70giyGp7zXMxWKc7tI/7ZJt3EbfXtsT4AjckT/sdOPutOPfCDAZTD4SgzKMiFPLZvLXYzXFqP0ZHsrwfZHOcOWTpP6AAlGz3AAm2yfBjQ+anbNkNMY+/M1vI2SzF1HBu5OwLt+25Pb5198bwn0hhoHQY/AVKMLnc5jrAxtLtgNyGkd9gO/zJm+Ftzwj7jQ2MfCSLNvbNrTMXNYy8zX+RWQIMbG4fwarPReN+/wBmMrgfhdhtdVasNGtFXrQx168TQyOKJoaxjR4AAdgPmURiSdK6lxWPqySnG5LqxGtLK6QRStYZGuYXEloLWvBaO2/KRsd+a8XLi4fs5jTeJ0wkiIi0oIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgL+OaHNIIBB7EH1r+og0tzRWAv2H2ZsNRNt1J+N8qbA1s7arzu6FsgAc1hPflBA3APiFjDRFeuB5Bk8tjSzFnFQiK66VkLPgzNZLzsMzfVI9rifB3MOyo0QTjsRqOo0+S6gitiPGCvG3JUWudJcHhZkdEYxs74UbGtG/dpb4Ka4bc/tFw3U5ep0Bzcvhvud9l0hc54dfuJxH+x/wC5Xodn+FX6x8ql8FGiLnMvshdAx6sj003OOsZiW8MYyKvSsSxus8wDohM2Mxlzd93AO9EAl22xWV4hHRkUBV48aHvZzI4itmJLF7GzWILwioWXR1HwNc6USyCPkZsGP2LiA7b0eZZOg+M+juJd+3R09lzau1Ymzy1bFWarL0idhI1kzGFzN+3M0EeHful4Fsi4hlvZP6fyWuNGae0hkquZfls27HXZHVJ+l0WwTOe+vNs2OQiSNjSWl4HMe3cFV7+PmgY9Ve152oYhkvKxQ5uhN5N5Tvt0PKOTo9Tftyc/Nv2237KZUDoCIuPccPZI6b4U4PU9avlK8+r8bjJLcOPfVnniZKWEwtsOiHLGHnbYPewkEbeIVmYjTI7Ci5xnOPejtF18XFqXMspZK1QjyEtetVnsGGJwG8sgiY/pR77jmfsOx79ithq3jVovREeLdlc4zmycPlNKKjBLdlnh2B6rY4GvcY9iPT25e/il4Fuim8HxF09qTMRYrG5EWb0uLhzLIhDI0OqSucyOXmLQO7mOHLvzDbuBuFOz+yG0BBQxFs5ySWPMRWJsfHBj7Ms1psEgjm5Imxl5LXH3u2+wLgC0EheB0ZFzfT3sjOHeqshi6eL1Gy1Jk5OhUl8knZBJNsXdHqujDBLsD9jLg/5lkZjj5oLAallwV/UMUF+GZlad3QmdXgldtyxy2AwxRvO49Fzwe47KXjWOgIudZ72QvD/TGYyWLyWf8nuYydla+0U7D2U3PaxzDM9sZbGwiRuz3ENJ3G+7XAYV3j3isfxx9zqeld6hx0Fpl6GjZma6aWUsbGSyItawN2JmLuQElpILXJeB1JFF6U4yaP1xqO3g8FlzkchVEpk6dWYQu6bwyTkmcwRycrnBp5HHYlWit7jS5L92WkP97n/6WZXqgsl+7LSH+9z/APSzK9WvtX6PT/aVnwERFwoIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAuc8Ov3E4j/Y/9yujLnPDr9xOI/2P/cr0Oz/Cr9Y+VS+CjXjDTgmwOpMBo3VLclgNGYHWsuSxV65p24yS1O+zMa8UtvlNcNdLOSJGuPO3kB5CXbez1zmD2PPD6vqj2wN0+H5IXDkAJbliSu2yXc/WEDpDEH8x5uYM337+KVRM9yInRmI1bpjhtxonwGJlq6ptajzd7EstwcnlL3bdGRoeAHg7DlJ9E7Dvsud4HR+a1Fr9s+Op69actonKYSXO6ujsN6eQk6L2jkf+sMHK4gta2Mu2DOYr2AiZI8pafvZbM1OBOm26A1NgrelcrBHlTZxT2U6/SoTwuc2YbsexzyCHtJHcbkEgHU8LuF1LHYbH8PtcaY4jXstXyLo556uQvnBWW+UGWO3u2YQNb715bsHBwPokr2GimSC8kayhzukNI8edHzaL1JmMpqmzkchi8piMY+3XtxWK7Wxxukb7x8XKWcjtjs0codv37q/2PHC+R7nv4e6Zc5x3LjioSSf/ACq8p04MfUgq1YWV60DGxRQxNDWsY0bBoA8AAANlZiZHnHH2Mrwj1rrLI39F5/UtfVGIxZoHEY91odSCqYZKk+36z6XpAv2b9kd3BBC0PCXS+pPY45nC3NTabzWpILmkcfifK8DTdkJMbYgfK+Ss5ke7gw9VuzwOUln9a9ZImSOD3M7kMBxvr63saS1JNic7pGtRihqY11ixWtR2ZpTBOxhIiJbM30nEM3a7dw2UdwA0hqHGZng9Pk9P5PGingtQR3BaqvZ5LJLeifGyQkbNc5oJaD74AkbheqUTJHljGaMz0XB3RdN2CyLLtbiYy/LXNOQSRVvPMrzO5u24j6bg7nPblO++y0uneGVTHzag0TrnTHEXLzZLO2n+UYa/f8z36tmwZGzSdOZsEezX/ZGuAPok7OJXsFFMkebs5o7LyaQ9k3Wjwt+V+VZMMZH5NI5139SIWN6PbeX02lo5d/SBHitjUdldD8ZtM529p7OX8ZktGU8KbOOoSWTWtx2C9zZw0bxjlk35nAD0XfEvQCK5I878IhlcBxYdh9LYbVWK0DKy9YyON1JjzDVx9oyhzHUZj3c2VzpHFjXOaAdxy77L0QiKxFhpcl+7LSH+9z/9LMr1QWS/dlpD/e5/+lmV6sO1fo9P9pWfAREXCgiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiIC51w+aYtIUIXdpIOpBI31teyRzHtPzhzSP6l0VTuW0PSyd2S3FavYyzLt1X0LBjEpHYFzDu0u2AHNtvsAN9gNuvAxKaYmirRe3K/VY1P4iw/c5b8os79ZZ+Ynuct+UWd+ss/MXRlYO3yktGtmIsP3OW/KLO/WWfmJ7nLflFnfrLPzEysHb5SWjWzEWH7nLflFnfrLPzE9zlvyizv1ln5iZWDt8pLRrZiLD9zlvyizv1ln5ie5y35RZ36yz8xMrB2+Ulo1sxFh+5y35RZ36yz8xPc5b8os79ZZ+YmVg7fKS0a2Yiw/c5b8os79ZZ+Ynuct+UWd+ss/MTKwdvlJaNbMRYfuct+UWd+ss/MT3OW/KLO/WWfmJlYO3yktGtmIsP3OW/KLO/WWfmJ7nLflFnfrLPzEysHb5SWjWzEWH7nLflFnfrLPzE9zlvyizv1ln5iZWDt8pLRrYV5pm1tpSNnpPjls2HNHiIxA5hd/NzSMH/wCQV4tRgtMU8AZZIXT2LMwAktW5XSyuA32bufBo3PojYdydtyVt1y4+JTiTEU90RbnM/UkREXMgiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiD//2Q==\n","text/plain":["<IPython.core.display.Image object>"]},"metadata":{}}]},{"cell_type":"code","source":["from pprint import pprint\n","\n","# Run\n","inputs = {\"question\": \"What is the AlphaCodium paper about?\"}\n","for output in app.stream(inputs):\n","    for key, value in output.items():\n","        # Node\n","        pprint(f\"Node '{key}':\")\n","        # Optional: print full state at each node\n","        # pprint.pprint(value[\"keys\"], indent=2, width=80, depth=None)\n","    pprint(\"\\n---\\n\")\n","\n","# Final generation\n","pprint(value[\"generation\"])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"TrGy5-Dso_dG","executionInfo":{"status":"ok","timestamp":1726989088229,"user_tz":-480,"elapsed":9596,"user":{"displayName":"李辉","userId":"12972001611808140221"}},"outputId":"d8a4a8ff-6033-4c64-84f4-0afe878eddfc"},"execution_count":26,"outputs":[{"output_type":"stream","name":"stdout","text":["---ROUTE QUESTION---\n","What is the AlphaCodium paper about?\n","{'datasource': 'web_search'}\n","web_search\n","---ROUTE QUESTION TO WEB SEARCH---\n","---WEB SEARCH---\n","\"Node 'web_search':\"\n","'\\n---\\n'\n","---GENERATE---\n","---CHECK HALLUCINATIONS---\n","---DECISION: GENERATION IS GROUNDED IN DOCUMENTS---\n","---GRADE GENERATION vs QUESTION---\n","---DECISION: GENERATION ADDRESSES QUESTION---\n","\"Node 'generate':\"\n","'\\n---\\n'\n","(' The AlphaCodium paper proposes a new approach for code generation by Large '\n"," 'Language Models (LLMs). It introduces a test-based, multi-stage, iterative '\n"," 'flow called AlphaCodium that improves the performance of LLMs on code '\n"," 'problems. This method was tested on the CodeContests dataset containing '\n"," \"around 10,000 competitive programming problems and outperformed DeepMind's \"\n"," 'AlphaCode and AlphaCode2 without fine-tuning a model. The full '\n"," 'implementation is available at https://github.com/Codium-ai/AlphaCodium.')\n"]}]},{"cell_type":"code","source":["# Run\n","inputs = {\"question\": \"What is agent memory?\"}\n","for output in app.stream(inputs):\n","    for key, value in output.items():\n","        # Node\n","        pprint(f\"Node '{key}':\")\n","        # Optional: print full state at each node\n","        # pprint.pprint(value[\"keys\"], indent=2, width=80, depth=None)\n","    pprint(\"\\n---\\n\")\n","\n","# Final generation\n","pprint(value[\"generation\"])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"e2Y-j4PZQHq6","executionInfo":{"status":"ok","timestamp":1726989194107,"user_tz":-480,"elapsed":4886,"user":{"displayName":"李辉","userId":"12972001611808140221"}},"outputId":"6637f9ec-c909-425a-94ea-dda7b7e9b337"},"execution_count":27,"outputs":[{"output_type":"stream","name":"stdout","text":["---ROUTE QUESTION---\n","What is agent memory?\n","{'datasource': 'vectorstore'}\n","vectorstore\n","---ROUTE QUESTION TO RAG---\n","---RETRIEVE---\n","\"Node 'retrieve':\"\n","'\\n---\\n'\n","---CHECK DOCUMENT RELEVANCE TO QUESTION---\n","---GRADE: DOCUMENT NOT RELEVANT---\n","---GRADE: DOCUMENT RELEVANT---\n","---GRADE: DOCUMENT RELEVANT---\n","---GRADE: DOCUMENT RELEVANT---\n","---ASSESS GRADED DOCUMENTS---\n","---DECISION: GENERATE---\n","\"Node 'grade_documents':\"\n","'\\n---\\n'\n","---GENERATE---\n","---CHECK HALLUCINATIONS---\n","---DECISION: GENERATION IS GROUNDED IN DOCUMENTS---\n","---GRADE GENERATION vs QUESTION---\n","---DECISION: GENERATION ADDRESSES QUESTION---\n","\"Node 'generate':\"\n","'\\n---\\n'\n","(' In an LLM (Large Language Model) powered autonomous agent system, long-term '\n"," 'memory refers to the capability of the agent to retain and recall '\n"," 'information over extended periods. This is often achieved by leveraging an '\n"," 'external vector store and fast retrieval.')\n"]}]}]}